Susceptible-infected-susceptible epidemics on networks with general infection and cure times

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Cator, E.; van de Bovenkamp, R.; Van Mieghem, P.

2013-06-01

The classical, continuous-time susceptible-infected-susceptible (SIS) Markov epidemic model on an arbitrary network is extended to incorporate infection and curing or recovery times each characterized by a general distribution (rather than an exponential distribution as in Markov processes). This extension, called the generalized SIS (GSIS) model, is believed to have a much larger applicability to real-world epidemics (such as information spread in online social networks, real diseases, malware spread in computer networks, etc.) that likely do not feature exponential times. While the exact governing equations for the GSIS model are difficult to deduce due to their non-Markovian nature, accurate mean-field equations are derived that resemble our previous N-intertwined mean-field approximation (NIMFA) and so allow us to transfer the whole analytic machinery of the NIMFA to the GSIS model. In particular, we establish the criterion to compute the epidemic threshold in the GSIS model. Moreover, we show that the average number of infection attempts during a recovery time is the more natural key parameter, instead of the effective infection rate in the classical, continuous-time SIS Markov model. The relative simplicity of our mean-field results enables us to treat more general types of SIS epidemics, while offering an easier key parameter to measure the average activity of those general viral agents.

Phylogenetic studies of transmission dynamics in generalized HIV epidemics: An essential tool where the burden is greatest?

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Dennis, Ann M.; Herbeck, Joshua T.; Brown, Andrew Leigh; Kellam, Paul; de Oliveira, Tulio; Pillay, Deenan; Fraser, Christophe; Cohen, Myron S.

2014-01-01

Efficient and effective HIV prevention measures for generalized epidemics in sub-Saharan Africa have not yet been validated at the population-level. Design and impact evaluation of such measures requires fine-scale understanding of local HIV transmission dynamics. The novel tools of HIV phylogenetics and molecular epidemiology may elucidate these transmission dynamics. Such methods have been incorporated into studies of concentrated HIV epidemics to identify proximate and determinant traits associated with ongoing transmission. However, applying similar phylogenetic analyses to generalized epidemics, including the design and evaluation of prevention trials, presents additional challenges. Here we review the scope of these methods and present examples of their use in concentrated epidemics in the context of prevention. Next, we describe the current uses for phylogenetics in generalized epidemics, and discuss their promise for elucidating transmission patterns and informing prevention trials. Finally, we review logistic and technical challenges inherent to large-scale molecular epidemiological studies of generalized epidemics, and suggest potential solutions. PMID:24977473

Phenotypic and Genotypic Comparison of Epidemic and Non-Epidemic Strains of Pseudomonas aeruginosa from Individuals with Cystic Fibrosis.

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Jessica Duong

Full Text Available Epidemic strains of Pseudomonas aeruginosa have been found worldwide among the cystic fibrosis (CF patient population. Using pulse-field gel electrophoresis, the Prairie Epidemic Strain (PES has recently been found in one-third of patients attending the Calgary Adult CF Clinic in Canada. Using multi-locus sequence typing, PES isolates from unrelated patients were found to consistently have ST192. Though most patients acquired PES prior to enrolling in the clinic, some patients were observed to experience strain replacement upon transitioning to the clinic whereby local non-epidemic P. aeruginosa isolates were displaced by PES. Here we genotypically and phenotypically compared PES to other P. aeruginosa epidemic strains (OES found around the world as well as local non-epidemic CF P. aeruginosa isolates in order to characterize PES. Since some epidemic strains are associated with worse clinical outcomes, we assessed the pathogenic potential of PES to determine if these isolates are virulent, shared properties with OES, and if its phenotypic properties may offer a competitive advantage in displacing local non-epidemic isolates during strain replacement. As such, we conducted a comparative analysis using fourteen phenotypic traits, including virulence factor production, biofilm formation, planktonic growth, mucoidy, and antibiotic susceptibility to characterize PES, OES, and local non-epidemic isolates. We observed that PES and OES could be differentiated from local non-epidemic isolates based on biofilm growth with PES isolates being more mucoid. Pairwise comparisons indicated that PES produced significantly higher levels of proteases and formed better biofilms than OES but were more susceptible to antibiotic treatment. Amongst five patients experiencing strain replacement, we found that super-infecting PES produced lower levels of proteases and elastases but were more resistant to antibiotics compared to the displaced non-epidemic isolates. This

Can influenza epidemics be prevented by voluntary vaccination?

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Raffaele Vardavas

2007-05-01

Full Text Available Previous modeling studies have identified the vaccination coverage level necessary for preventing influenza epidemics, but have not shown whether this critical coverage can be reached. Here we use computational modeling to determine, for the first time, whether the critical coverage for influenza can be achieved by voluntary vaccination. We construct a novel individual-level model of human cognition and behavior; individuals are characterized by two biological attributes (memory and adaptability that they use when making vaccination decisions. We couple this model with a population-level model of influenza that includes vaccination dynamics. The coupled models allow individual-level decisions to influence influenza epidemiology and, conversely, influenza epidemiology to influence individual-level decisions. By including the effects of adaptive decision-making within an epidemic model, we can reproduce two essential characteristics of influenza epidemiology: annual variation in epidemic severity and sporadic occurrence of severe epidemics. We suggest that individual-level adaptive decision-making may be an important (previously overlooked causal factor in driving influenza epidemiology. We find that severe epidemics cannot be prevented unless vaccination programs offer incentives. Frequency of severe epidemics could be reduced if programs provide, as an incentive to be vaccinated, several years of free vaccines to individuals who pay for one year of vaccination. Magnitude of epidemic amelioration will be determined by the number of years of free vaccination, an individuals' adaptability in decision-making, and their memory. This type of incentive program could control epidemics if individuals are very adaptable and have long-term memories. However, incentive-based programs that provide free vaccination for families could increase the frequency of severe epidemics. We conclude that incentive-based vaccination programs are necessary to control

Dynamical processes and epidemic threshold on nonlinear coupled multiplex networks

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Gao, Chao; Tang, Shaoting; Li, Weihua; Yang, Yaqian; Zheng, Zhiming

2018-04-01

Recently, the interplay between epidemic spreading and awareness diffusion has aroused the interest of many researchers, who have studied models mainly based on linear coupling relations between information and epidemic layers. However, in real-world networks the relation between two layers may be closely correlated with the property of individual nodes and exhibits nonlinear dynamical features. Here we propose a nonlinear coupled information-epidemic model (I-E model) and present a comprehensive analysis in a more generalized scenario where the upload rate differs from node to node, deletion rate varies between susceptible and infected states, and infection rate changes between unaware and aware states. In particular, we develop a theoretical framework of the intra- and inter-layer dynamical processes with a microscopic Markov chain approach (MMCA), and derive an analytic epidemic threshold. Our results suggest that the change of upload and deletion rate has little effect on the diffusion dynamics in the epidemic layer.

The impact of multiple information on coupled awareness-epidemic dynamics in multiplex networks

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Pan, Yaohui; Yan, Zhijun

2018-02-01

Growing interest has emerged in the study of the interplay between awareness and epidemics in multiplex networks. However, previous studies on this issue usually assume that all aware individuals take the same level of precautions, ignoring individual heterogeneity. In this paper, we investigate the coupled awareness-epidemic dynamics in multiplex networks considering individual heterogeneity. Here, the precaution levels are heterogeneous and depend on three types of information: contact information and local and global prevalence information. The results show that contact-based precautions can decrease the epidemic prevalence and augment the epidemic threshold, but prevalence-based precautions, regardless of local or global information, can only decrease the epidemic prevalence. Moreover, unlike previous studies in single-layer networks, we do not find a greater impact of local prevalence information on the epidemic prevalence compared to global prevalence information. In addition, we find that the altruistic behaviors of infected individuals can effectively suppress epidemic spreading, especially when the level of contact-based precaution is high.

Epidemic spreading in weighted networks: an edge-based mean-field solution.

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Yang, Zimo; Zhou, Tao

2012-05-01

Weight distribution greatly impacts the epidemic spreading taking place on top of networks. This paper presents a study of a susceptible-infected-susceptible model on regular random networks with different kinds of weight distributions. Simulation results show that the more homogeneous weight distribution leads to higher epidemic prevalence, which, unfortunately, could not be captured by the traditional mean-field approximation. This paper gives an edge-based mean-field solution for general weight distribution, which can quantitatively reproduce the simulation results. This method could be applied to characterize the nonequilibrium steady states of dynamical processes on weighted networks.

MOSES: A Matlab-based open-source stochastic epidemic simulator.

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Varol, Huseyin Atakan

2016-08-01

This paper presents an open-source stochastic epidemic simulator. Discrete Time Markov Chain based simulator is implemented in Matlab. The simulator capable of simulating SEQIJR (susceptible, exposed, quarantined, infected, isolated and recovered) model can be reduced to simpler models by setting some of the parameters (transition probabilities) to zero. Similarly, it can be extended to more complicated models by editing the source code. It is designed to be used for testing different control algorithms to contain epidemics. The simulator is also designed to be compatible with a network based epidemic simulator and can be used in the network based scheme for the simulation of a node. Simulations show the capability of reproducing different epidemic model behaviors successfully in a computationally efficient manner.

Susceptible-infected-recovered epidemics in random networks with population awareness

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Wu, Qingchu; Chen, Shufang

2017-10-01

The influence of epidemic information-based awareness on the spread of infectious diseases on networks cannot be ignored. Within the effective degree modeling framework, we discuss the susceptible-infected-recovered model in complex networks with general awareness and general degree distribution. By performing the linear stability analysis, the conditions of epidemic outbreak can be deduced and the results of the previous research can be further expanded. Results show that the local awareness can suppress significantly the epidemic spreading on complex networks via raising the epidemic threshold and such effects are closely related to the formulation of awareness functions. In addition, our results suggest that the recovered information-based awareness has no effect on the critical condition of epidemic outbreak.

Data and methods to characterize the role of sex work and to inform sex work programs in generalized HIV epidemics: evidence to challenge assumptions.

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Mishra, Sharmistha; Boily, Marie-Claude; Schwartz, Sheree; Beyrer, Chris; Blanchard, James F; Moses, Stephen; Castor, Delivette; Phaswana-Mafuya, Nancy; Vickerman, Peter; Drame, Fatou; Alary, Michel; Baral, Stefan D

2016-08-01

In the context of generalized human immunodeficiency virus (HIV) epidemics, there has been limited recent investment in HIV surveillance and prevention programming for key populations including female sex workers. Often implicit in the decision to limit investment in these epidemic settings are assumptions including that commercial sex is not significant to the sustained transmission of HIV, and HIV interventions designed to reach "all segments of society" will reach female sex workers and clients. Emerging empiric and model-based evidence is challenging these assumptions. This article highlights the frameworks and estimates used to characterize the role of sex work in HIV epidemics as well as the relevant empiric data landscape on sex work in generalized HIV epidemics and their strengths and limitations. Traditional approaches to estimate the contribution of sex work to HIV epidemics do not capture the potential for upstream and downstream sexual and vertical HIV transmission. Emerging approaches such as the transmission population attributable fraction from dynamic mathematical models can address this gap. To move forward, the HIV scientific community must begin by replacing assumptions about the epidemiology of generalized HIV epidemics with data and more appropriate methods of estimating the contribution of unprotected sex in the context of sex work. Copyright © 2016 Elsevier Inc. All rights reserved.

Epidemic spreading in a hierarchical social network.

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Grabowski, A; Kosiński, R A

2004-09-01

A model of epidemic spreading in a population with a hierarchical structure of interpersonal interactions is described and investigated numerically. The structure of interpersonal connections is based on a scale-free network. Spatial localization of individuals belonging to different social groups, and the mobility of a contemporary community, as well as the effectiveness of different interpersonal interactions, are taken into account. Typical relations characterizing the spreading process, like a range of epidemic and epidemic curves, are discussed. The influence of preventive vaccinations on the spreading process is investigated. The critical value of preventively vaccinated individuals that is sufficient for the suppression of an epidemic is calculated. Our results are compared with solutions of the master equation for the spreading process and good agreement of the character of this process is found.

Epidemics spread in heterogeneous populations

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Capała, Karol; Dybiec, Bartłomiej

2017-05-01

Individuals building populations are subject to variability. This variability affects progress of epidemic outbreaks, because individuals tend to be more or less resistant. Individuals also differ with respect to their recovery rate. Here, properties of the SIR model in inhomogeneous populations are studied. It is shown that a small change in model's parameters, e.g. recovery or infection rate, can substantially change properties of final states which is especially well-visible in distributions of the epidemic size. In addition to the epidemic size and radii distributions, the paper explores first passage time properties of epidemic outbreaks.

An epidemic model for the future progression of the current Haiti cholera epidemic

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Bertuzzo, E.; Mari, L.; Righetto, L.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

2012-04-01

As a major cholera epidemic progresses in Haiti, and the figures of the infection, up to December 2011, climb to 522,000 cases and 7,000 deaths, the development of general models to track and predict the evolution of the outbreak, so as to guide the allocation of medical supplies and staff, is gaining notable urgency. We propose here a spatially explicit epidemic model that accounts for the dynamics of susceptible and infected individuals as well as the redistribution of Vibrio cholera, the causative agent of the disease, among different human communities. In particular, we model two spreading pathways: the advection of pathogens through hydrologic connections and the dissemination due to human mobility described by means of a gravity-like model. To this end the country has been divided into hydrologic units based on drainage directions derived from a digital terrain model. Moreover the population of each unit has been estimated from census data downscaled to 1 km x 1 km resolution via remotely sensed geomorphological information (LandScan project). The model directly accounts for the role of rainfall patterns in driving the seasonality of cholera outbreaks. The two main outbreaks in fact occurred during the rainy seasons (October and May) when extensive floodings severely worsened the sanitation conditions and, in turn, raised the risk of infection. The model capability to reproduce the spatiotemporal features of the epidemic up to date grants robustness to the foreseen future development. To this end, we generate realistic scenario of future precipitation in order to forecast possible epidemic paths up to the end of the 2013. In this context, the duration of acquired immunity, a hotly debated topic in the scientific community, emerges as a controlling factor for progression of the epidemic in the near future. The framework presented here can straightforwardly be used to evaluate the effectiveness of alternative intervention strategies like mass vaccinations

Utility and potential of rapid epidemic intelligence from internet-based sources.

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Yan, S J; Chughtai, A A; Macintyre, C R

2017-10-01

Rapid epidemic detection is an important objective of surveillance to enable timely intervention, but traditional validated surveillance data may not be available in the required timeframe for acute epidemic control. Increasing volumes of data on the Internet have prompted interest in methods that could use unstructured sources to enhance traditional disease surveillance and gain rapid epidemic intelligence. We aimed to summarise Internet-based methods that use freely-accessible, unstructured data for epidemic surveillance and explore their timeliness and accuracy outcomes. Steps outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist were used to guide a systematic review of research related to the use of informal or unstructured data by Internet-based intelligence methods for surveillance. We identified 84 articles published between 2006-2016 relating to Internet-based public health surveillance methods. Studies used search queries, social media posts and approaches derived from existing Internet-based systems for early epidemic alerts and real-time monitoring. Most studies noted improved timeliness compared to official reporting, such as in the 2014 Ebola epidemic where epidemic alerts were generated first from ProMED-mail. Internet-based methods showed variable correlation strength with official datasets, with some methods showing reasonable accuracy. The proliferation of publicly available information on the Internet provided a new avenue for epidemic intelligence. Methodologies have been developed to collect Internet data and some systems are already used to enhance the timeliness of traditional surveillance systems. To improve the utility of Internet-based systems, the key attributes of timeliness and data accuracy should be included in future evaluations of surveillance systems. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

The third therapeutic system: faith healing strategies in the context of a generalized AIDS epidemic.

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Manglos, Nicolette D; Trinitapoli, Jenny

2011-03-01

Faith healing in sub-Saharan Africa has primarily been studied qualitatively among Pentecostal-Charismatic groups, and considered as its own phenomenon with little attention to its relationship to other modes of healing. Using data from Malawi, a religiously diverse African country with high HIV prevalence, we find that faith healing is pervasive across multiple religious traditions. For individuals, attending a faith healing congregation is associated with lower levels of generalized worry about AIDS, and this association is driven by those who switched churches before AIDS became widespread in rural areas. Use of condoms and traditional medicine are, on the other hand, positively associated with worry about AIDS. We argue that faith healing can be understood as a third therapeutic system that coexists with the well-documented biomedical and traditional systems. The success of faith healing approaches lies in their unique ability to combine individual-pragmatic and communal-ritualized aspects of healing to inform interpretations of the AIDS epidemic and its consequences.

The Third Therapeutic System: Faith Healing Strategies in the Context of a Generalized AIDS Epidemic

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Manglos, Nicolette D.; Trinitapoli, Jenny

2014-01-01

Faith healing in sub-Saharan Africa has primarily been studied qualitatively among Pentecostal-Charismatic groups, and considered as its own phenomenon with little attention to its relationship to other modes of healing. Using data from Malawi, a religiously diverse African country with high HIV prevalence, we find that faith healing is pervasive across multiple religious traditions. For individuals, attending a faith healing congregation is associated with lower levels of generalized worry about AIDS, and this association is driven by those who switched churches before AIDS became widespread in rural areas. Use of condoms and traditional medicine are, on the other hand, positively associated with worry about AIDS. We argue that faith healing can be understood as a third therapeutic system that coexists with the well-documented biomedical and traditional systems. The success of faith healing approaches lies in their unique ability to combine individual-pragmatic and communal-ritualized aspects of healing to inform interpretations of the AIDS epidemic and its consequences. PMID:21362615

Nonlinear model of epidemic spreading in a complex social network.

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Kosiński, Robert A; Grabowski, A

2007-10-01

The epidemic spreading in a human society is a complex process, which can be described on the basis of a nonlinear mathematical model. In such an approach the complex and hierarchical structure of social network (which has implications for the spreading of pathogens and can be treated as a complex network), can be taken into account. In our model each individual has one of the four permitted states: susceptible, infected, infective, unsusceptible or dead. This refers to the SEIR model used in epidemiology. The state of an individual changes in time, depending on the previous state and the interactions with other individuals. The description of the interpersonal contacts is based on the experimental observations of the social relations in the community. It includes spatial localization of the individuals and hierarchical structure of interpersonal interactions. Numerical simulations were performed for different types of epidemics, giving the progress of a spreading process and typical relationships (e.g. range of epidemic in time, the epidemic curve). The spreading process has a complex and spatially chaotic character. The time dependence of the number of infective individuals shows the nonlinear character of the spreading process. We investigate the influence of the preventive vaccinations on the spreading process. In particular, for a critical value of preventively vaccinated individuals the percolation threshold is observed and the epidemic is suppressed.

Epidemic Spreading with Heterogeneous Awareness on Human Networks

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Yanling Lu

2017-01-01

Full Text Available The spontaneous awareness behavioral responses of individuals have a significant impact on epidemic spreading. In this paper, a modified Susceptible-Alert-Infected-Susceptible (SAIS epidemic model with heterogeneous awareness is presented to study epidemic spreading in human networks and the impact of heterogeneous awareness on epidemic dynamics. In this model, when susceptible individuals receive awareness information about the presence of epidemic from their infected neighbor nodes, they will become alert individuals with heterogeneous awareness rate. Theoretical analysis and numerical simulations show that heterogeneous awareness can enhance the epidemic threshold with certain conditions and reduce the scale of virus outbreaks compared with no awareness. What is more, for the same awareness parameter, it also shows that heterogeneous awareness can slow effectively the spreading size and does not delay the arrival time of epidemic spreading peak compared with homogeneous awareness.

Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.

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Takaguchi, Taro; Masuda, Naoki; Holme, Petter

2013-01-01

Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.

Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.

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Taro Takaguchi

Full Text Available Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.

Leveraging social networks for understanding the evolution of epidemics

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2011-01-01

Background To understand how infectious agents disseminate throughout a population it is essential to capture the social model in a realistic manner. This paper presents a novel approach to modeling the propagation of the influenza virus throughout a realistic interconnection network based on actual individual interactions which we extract from online social networks. The advantage is that these networks can be extracted from existing sources which faithfully record interactions between people in their natural environment. We additionally allow modeling the characteristics of each individual as well as customizing his daily interaction patterns by making them time-dependent. Our purpose is to understand how the infection spreads depending on the structure of the contact network and the individuals who introduce the infection in the population. This would help public health authorities to respond more efficiently to epidemics. Results We implement a scalable, fully distributed simulator and validate the epidemic model by comparing the simulation results against the data in the 2004-2005 New York State Department of Health Report (NYSDOH), with similar temporal distribution results for the number of infected individuals. We analyze the impact of different types of connection models on the virus propagation. Lastly, we analyze and compare the effects of adopting several different vaccination policies, some of them based on individual characteristics -such as age- while others targeting the super-connectors in the social model. Conclusions This paper presents an approach to modeling the propagation of the influenza virus via a realistic social model based on actual individual interactions extracted from online social networks. We implemented a scalable, fully distributed simulator and we analyzed both the dissemination of the infection and the effect of different vaccination policies on the progress of the epidemics. The epidemic values predicted by our simulator match

Leveraging social networks for understanding the evolution of epidemics

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Martín Gonzalo

2011-12-01

Full Text Available Abstract Background To understand how infectious agents disseminate throughout a population it is essential to capture the social model in a realistic manner. This paper presents a novel approach to modeling the propagation of the influenza virus throughout a realistic interconnection network based on actual individual interactions which we extract from online social networks. The advantage is that these networks can be extracted from existing sources which faithfully record interactions between people in their natural environment. We additionally allow modeling the characteristics of each individual as well as customizing his daily interaction patterns by making them time-dependent. Our purpose is to understand how the infection spreads depending on the structure of the contact network and the individuals who introduce the infection in the population. This would help public health authorities to respond more efficiently to epidemics. Results We implement a scalable, fully distributed simulator and validate the epidemic model by comparing the simulation results against the data in the 2004-2005 New York State Department of Health Report (NYSDOH, with similar temporal distribution results for the number of infected individuals. We analyze the impact of different types of connection models on the virus propagation. Lastly, we analyze and compare the effects of adopting several different vaccination policies, some of them based on individual characteristics -such as age- while others targeting the super-connectors in the social model. Conclusions This paper presents an approach to modeling the propagation of the influenza virus via a realistic social model based on actual individual interactions extracted from online social networks. We implemented a scalable, fully distributed simulator and we analyzed both the dissemination of the infection and the effect of different vaccination policies on the progress of the epidemics. The epidemic values

Inhomogeneity of epidemic spreading with entropy-based infected clusters.

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Wen-Jie, Zhou; Xing-Yuan, Wang

2013-12-01

Considering the difference in the sizes of the infected clusters in the dynamic complex networks, the normalized entropy based on infected clusters (δ*) is proposed to characterize the inhomogeneity of epidemic spreading. δ* gives information on the variability of the infected clusters in the system. We investigate the variation in the inhomogeneity of the distribution of the epidemic with the absolute velocity v of moving agent, the infection density ρ, and the interaction radius r. By comparing δ* in the dynamic networks with δH* in homogeneous mode, the simulation experiments show that the inhomogeneity of epidemic spreading becomes smaller with the increase of v, ρ, r.

Planning horizon affects prophylactic decision-making and epidemic dynamics.

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Nardin, Luis G; Miller, Craig R; Ridenhour, Benjamin J; Krone, Stephen M; Joyce, Paul; Baumgaertner, Bert O

2016-01-01

The spread of infectious diseases can be impacted by human behavior, and behavioral decisions often depend implicitly on a planning horizon-the time in the future over which options are weighed. We investigate the effects of planning horizons on epidemic dynamics. We developed an epidemiological agent-based model (along with an ODE analog) to explore the decision-making of self-interested individuals on adopting prophylactic behavior. The decision-making process incorporates prophylaxis efficacy and disease prevalence with the individuals' payoffs and planning horizon. Our results show that for short and long planning horizons individuals do not consider engaging in prophylactic behavior. In contrast, individuals adopt prophylactic behavior when considering intermediate planning horizons. Such adoption, however, is not always monotonically associated with the prevalence of the disease, depending on the perceived protection efficacy and the disease parameters. Adoption of prophylactic behavior reduces the epidemic peak size while prolonging the epidemic and potentially generates secondary waves of infection. These effects can be made stronger by increasing the behavioral decision frequency or distorting an individual's perceived risk of infection.

Disease spreading with epidemic alert on small-world networks

International Nuclear Information System (INIS)

Han, Xiao-Pu

2007-01-01

Base on two-dimension small-world networks, a susceptible-infected model with epidemic alert is proposed in this Letter. In this model, if some parts of the network are alarmed as dangerous, a fraction of edges between the alarmed parts and others will be removed, and two cases of alerting rules that the degree and frequency of contacts kept unchanged are considered respectively. The numerical simulations show that the spreading velocity is reduced by the accurate and timely epidemic alert, and the more accurate and timely, the stronger the deceleration effect. This model indicates that to broadcast epidemic alert timely is helpful and necessary in the control of epidemic spreading, and in agreement with the general view of epidemic alert. This work is helpful to understand the effects of epidemic alert on disease spreading

Disease-induced resource constraints can trigger explosive epidemics

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Böttcher, L.; Woolley-Meza, O.; Araújo, N. A. M.; Herrmann, H. J.; Helbing, D.

2015-11-01

Advances in mathematical epidemiology have led to a better understanding of the risks posed by epidemic spreading and informed strategies to contain disease spread. However, a challenge that has been overlooked is that, as a disease becomes more prevalent, it can limit the availability of the capital needed to effectively treat those who have fallen ill. Here we use a simple mathematical model to gain insight into the dynamics of an epidemic when the recovery of sick individuals depends on the availability of healing resources that are generated by the healthy population. We find that epidemics spiral out of control into “explosive” spread if the cost of recovery is above a critical cost. This can occur even when the disease would die out without the resource constraint. The onset of explosive epidemics is very sudden, exhibiting a discontinuous transition under very general assumptions. We find analytical expressions for the critical cost and the size of the explosive jump in infection levels in terms of the parameters that characterize the spreading process. Our model and results apply beyond epidemics to contagion dynamics that self-induce constraints on recovery, thereby amplifying the spreading process.

A class of stochastic delayed SIR epidemic models with generalized nonlinear incidence rate and temporary immunity

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Fan, Kuangang; Zhang, Yan; Gao, Shujing; Wei, Xiang

2017-09-01

A class of SIR epidemic model with generalized nonlinear incidence rate is presented in this paper. Temporary immunity and stochastic perturbation are also considered. The existence and uniqueness of the global positive solution is achieved. Sufficient conditions guaranteeing the extinction and persistence of the epidemic disease are established. Moreover, the threshold behavior is discussed, and the threshold value R0 is obtained. We show that if R0 extinct with probability one, whereas if R0 > 1, then the system remains permanent in the mean.

EpSoc: Social-Based Epidemic-Based Routing Protocol in Opportunistic Mobile Social Network

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Halikul Lenando

2018-01-01

Full Text Available In opportunistic networks, the nature of intermittent and disruptive connections degrades the efficiency of routing. Epidemic routing protocol is used as a benchmark for most of routing protocols in opportunistic mobile social networks (OMSNs due to its high message delivery and latency. However, Epidemic incurs high cost in terms of overhead and hop count. In this paper, we propose a hybrid routing protocol called EpSoc which utilizes the Epidemic routing forwarding strategy and exploits an important social feature, that is, degree centrality. Two techniques are used in EpSoc. Messages’ TTL is adjusted based on the degree centrality of nodes, and the message blocking mechanism is used to control replication. Simulation results show that EpSoc increases the delivery ratio and decreases the overhead ratio, the average latency, and the hop counts as compared to Epidemic and Bubble Rap.

A qualitative view of the HIV epidemic in coastal Ecuador.

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Beckman, Adam L; Wilson, Magdalena M; Prabhu, Vishaal; Soekoe, Nicola; Mata, Humberto; Grau, Lauretta E

2016-01-01

In 2013 approximately 37,000 people were living with HIV in Ecuador (prevalence 0.4%), representing a generalized epidemic where most new infections arise from sexual interactions in the general population. Studies that examine attitudes towards people living with HIV (PLWH), individual risk perception of acquiring HIV amongst Ecuadorians, and the ways in which levels of risk perception may affect risk behaviors are lacking. This qualitative study aimed to fill this gap in the literature by investigating these issues in the rural, coastal community of Manglaralto, Ecuador, which has among the highest incidence of HIV in Ecuador. We conducted interviews with 15 patients at Manglaralto Hospital. Analysis of interview transcripts revealed widespread negative attitudes towards PLWH, prevalent risk behaviors such as multiple sex partners and lack of condom use, and low individual risk-perception of contracting HIV. These findings underscore the need for increased efforts to prevent further growth of the HIV epidemic in Ecuador.

A qualitative view of the HIV epidemic in coastal Ecuador

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Adam L. Beckman

2016-11-01

Full Text Available In 2013 approximately 37,000 people were living with HIV in Ecuador (prevalence 0.4%, representing a generalized epidemic where most new infections arise from sexual interactions in the general population. Studies that examine attitudes towards people living with HIV (PLWH, individual risk perception of acquiring HIV amongst Ecuadorians, and the ways in which levels of risk perception may affect risk behaviors are lacking. This qualitative study aimed to fill this gap in the literature by investigating these issues in the rural, coastal community of Manglaralto, Ecuador, which has among the highest incidence of HIV in Ecuador. We conducted interviews with 15 patients at Manglaralto Hospital. Analysis of interview transcripts revealed widespread negative attitudes towards PLWH, prevalent risk behaviors such as multiple sex partners and lack of condom use, and low individual risk-perception of contracting HIV. These findings underscore the need for increased efforts to prevent further growth of the HIV epidemic in Ecuador.

Halting HIV/AIDS with avatars and havatars: a virtual world approach to modelling epidemics

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Smith? Robert J

2009-11-01

Full Text Available Abstract Background A major deficit of all approaches to epidemic modelling to date has been the need to approximate or guess at human behaviour in disease-transmission-related contexts. Avatars are generally human-like figures in virtual computer worlds controlled by human individuals. Methods We introduce the concept of a "havatar", which is a (human, avatar pairing. Evidence is mounting that this pairing behaves in virtual contexts much like the human in the pairing might behave in analogous real-world contexts. Results We propose that studies of havatars, in a virtual world, may give a realistic approximation of human behaviour in real-world contexts. If the virtual world approximates the real world in relevant details (geography, transportation, etc., virtual epidemics in that world could accurately simulate real-world epidemics. Havatar modelling of epidemics therefore offers a complementary tool for tackling how best to halt epidemics, including perhaps HIV/AIDS, since sexual behaviour is a significant component of some virtual worlds, such as Second Life. Conclusion Havatars place the control parameters of an epidemic in the hands of each individual. By providing tools that everyone can understand and use, we could democratise epidemiology.

Different Epidemic Models on Complex Networks

International Nuclear Information System (INIS)

Zhang Haifeng; Small, Michael; Fu Xinchu

2009-01-01

Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and similarly, the infected individuals can be sorted into different classes according to their infectivity. Moreover, some diseases may develop through several stages. Many authors have shown that the individuals' relation can be viewed as a complex network. So in this paper, in order to better explain the dynamical behavior of epidemics, we consider different epidemic models on complex networks, and obtain the epidemic threshold for each case. Finally, we present numerical simulations for each case to verify our results.

On the existence of a threshold for preventive behavioral responses to suppress epidemic spreading.

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Sahneh, Faryad Darabi; Chowdhury, Fahmida N; Scoglio, Caterina M

2012-01-01

The spontaneous behavioral responses of individuals to the progress of an epidemic are recognized to have a significant impact on how the infection spreads. One observation is that, even if the infection strength is larger than the classical epidemic threshold, the initially growing infection can diminish as the result of preventive behavioral patterns adopted by the individuals. In order to investigate such dynamics of the epidemic spreading, we use a simple behavioral model coupled with the individual-based SIS epidemic model where susceptible individuals adopt a preventive behavior when sensing infection. We show that, given any infection strength and contact topology, there exists a region in the behavior-related parameter space such that infection cannot survive in long run and is completely contained. Several simulation results, including a spreading scenario in a realistic contact network from a rural district in the State of Kansas, are presented to support our analytical arguments.

Random migration processes between two stochastic epidemic centers.

Science.gov (United States)

Sazonov, Igor; Kelbert, Mark; Gravenor, Michael B

2016-04-01

We consider the epidemic dynamics in stochastic interacting population centers coupled by random migration. Both the epidemic and the migration processes are modeled by Markov chains. We derive explicit formulae for the probability distribution of the migration process, and explore the dependence of outbreak patterns on initial parameters, population sizes and coupling parameters, using analytical and numerical methods. We show the importance of considering the movement of resident and visitor individuals separately. The mean field approximation for a general migration process is derived and an approximate method that allows the computation of statistical moments for networks with highly populated centers is proposed and tested numerically. Copyright © 2016 Elsevier Inc. All rights reserved.

Efficient local behavioral-change strategies to reduce the spread of epidemics in networks

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Bu, Yilei; Gregory, Steve; Mills, Harriet L.

2013-10-01

It has recently become established that the spread of infectious diseases between humans is affected not only by the pathogen itself but also by changes in behavior as the population becomes aware of the epidemic, for example, social distancing. It is also well known that community structure (the existence of relatively densely connected groups of vertices) in contact networks influences the spread of disease. We propose a set of local strategies for social distancing, based on community structure, that can be employed in the event of an epidemic to reduce the epidemic size. Unlike most social distancing methods, ours do not require individuals to know the disease state (infected or susceptible, etc.) of others, and we do not make the unrealistic assumption that the structure of the entire contact network is known. Instead, the recommended behavior change is based only on an individual's local view of the network. Each individual avoids contact with a fraction of his/her contacts, using knowledge of his/her local network to decide which contacts should be avoided. If the behavior change occurs only when an individual becomes ill or aware of the disease, these strategies can substantially reduce epidemic size with a relatively small cost, measured by the number of contacts avoided.

Epidemic propagation on adaptive coevolutionary networks with preferential local-world reconnecting strategy

International Nuclear Information System (INIS)

Song Yu-Rong; Jiang Guo-Ping; Gong Yong-Wang

2013-01-01

In the propagation of an epidemic in a population, individuals adaptively adjust their behavior to avoid the risk of an epidemic. Differently from existing studies where new links are established randomly, a local link is established preferentially in this paper. We propose a new preferentially reconnecting edge strategy depending on spatial distance (PR-SD). For the PR-SD strategy, the new link is established at random with probability p and in a shortest distance with the probability 1 − p. We establish the epidemic model on an adaptive network using Cellular Automata, and demonstrate the effectiveness of the proposed model by numerical simulations. The results show that the smaller the value of parameter p, the more difficult the epidemic spread is. The PR-SD strategy breaks long-range links and establishes as many short-range links as possible, which causes the network efficiency to decrease quickly and the propagation of the epidemic is restrained effectively. (general)

Interplay Between Hiv/aids Epidemics and Demographic Structures Based on Sexual Contact Networks

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Bai, Wen-Jie; Zhou, Tao; Wang, Bing-Hong

In this article, we propose a network spreading model for HIV epidemics, wherein each individual is represented by a node of the transmission network and the edges are the connections between individuals along which the infection may spread. The sexual activity of each individual, measured by its degree, is not homogeneous but obeys a power-law distribution. Due to the heterogeneity of activity, the infection can persistently exist at a very low prevalence, which has been observed in the real data but cannot be illuminated by previous models with homogeneous mixing hypothesis. The model displays a clear picture of hierarchical spread: In the early stage the infection is adhered to these high-risk persons, and then, diffuses toward low-risk population. Furthermore, we find that to reduce the risky behaviors is much more effective in the fight against HIV/AIDS rather than the antiretroviral drug therapies. The prediction results show that the development of epidemics can be roughly categorized into three patterns for different countries, and the pattern of a given country is mainly determined by the average sex-activity and transmission probability per sexual partner. In most cases, the effect of HIV epidemics on demographic structure is very small. However, for some extremely countries, like Botswana, the number of sex-active people can be depressed to nearly a half by AIDS.

Two-stage effects of awareness cascade on epidemic spreading in multiplex networks

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Guo, Quantong; Jiang, Xin; Lei, Yanjun; Li, Meng; Ma, Yifang; Zheng, Zhiming

2015-01-01

Human awareness plays an important role in the spread of infectious diseases and the control of propagation patterns. The dynamic process with human awareness is called awareness cascade, during which individuals exhibit herd-like behavior because they are making decisions based on the actions of other individuals [Borge-Holthoefer et al., J. Complex Networks 1, 3 (2013), 10.1093/comnet/cnt006]. In this paper, to investigate the epidemic spreading with awareness cascade, we propose a local awareness controlled contagion spreading model on multiplex networks. By theoretical analysis using a microscopic Markov chain approach and numerical simulations, we find the emergence of an abrupt transition of epidemic threshold βc with the local awareness ratio α approximating 0.5 , which induces two-stage effects on epidemic threshold and the final epidemic size. These findings indicate that the increase of α can accelerate the outbreak of epidemics. Furthermore, a simple 1D lattice model is investigated to illustrate the two-stage-like sharp transition at αc≈0.5 . The results can give us a better understanding of why some epidemics cannot break out in reality and also provide a potential access to suppressing and controlling the awareness cascading systems.

Impulsive vaccination and dispersal on dynamics of an SIR epidemic model with restricting infected individuals boarding transports

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Jiao, Jianjun; Cai, Shaohong; Li, Limei

2016-05-01

To understand the effect of impulsive vaccination and restricting infected individuals boarding transports on disease spread, we establish an SIR model with impulsive vaccination, impulsive dispersal and restricting infected individuals boarding transports. This SIR epidemic model for two regions, which are connected by transportation of non-infected individuals, portrays the evolvement of diseases. We prove that all solutions of the investigated system are uniformly ultimately bounded. We also prove that there exists globally asymptotically stable infection-free boundary periodic solution. The condition for permanence is discussed. It is concluded that the approach of impulsive vaccination and restricting infected individuals boarding transports provides reliable tactic basis for preventing disease spread.

Deep assessment: an exploratory study of game-based, multimodal learning in Epidemic

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Jennifer Jenson

2016-03-01

Full Text Available n this study, we examine what and how intermediate age students learned from playing in a health-focused game-based digital learning environment, Epidemic. Epidemic is a playful interactive environment designed to deliver factual knowledge, invite critical understanding, and encourage effective self-care practices in dealing with viral contagious diseases, using a social networking interface to integrate both serious games and game-like multimodal design projects. Epidemic invites a playful approach to its deadly serious core concern – communicable disease – in order to see what happens when students are encouraged to critically approach information from multiple or contradictory perspectives. To identify what participants learned while interacting within Epidemic, we deployed two instructional and assessment models, noting the differences each instructional approach could potentially make, and what approach to assessment might help us evaluate game-based learning. We found that each approach provided importantly different perspectives on what and how students learned, and on the very meaning of student success. Recognizing that traditional assessment tools based in print-cultural literacy may prove increasingly ill-suited for assessing emergent multimodal literacies in game-based learning environments, this study seeks to contribute to a growing body of work on the development of novel assessments for learning.

A Data-Driven Air Transportation Delay Propagation Model Using Epidemic Process Models

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B. Baspinar

2016-01-01

Full Text Available In air transport network management, in addition to defining the performance behavior of the system’s components, identification of their interaction dynamics is a delicate issue in both strategic and tactical decision-making process so as to decide which elements of the system are “controlled” and how. This paper introduces a novel delay propagation model utilizing epidemic spreading process, which enables the definition of novel performance indicators and interaction rates of the elements of the air transportation network. In order to understand the behavior of the delay propagation over the network at different levels, we have constructed two different data-driven epidemic models approximating the dynamics of the system: (a flight-based epidemic model and (b airport-based epidemic model. The flight-based epidemic model utilizing SIS epidemic model focuses on the individual flights where each flight can be in susceptible or infected states. The airport-centric epidemic model, in addition to the flight-to-flight interactions, allows us to define the collective behavior of the airports, which are modeled as metapopulations. In network model construction, we have utilized historical flight-track data of Europe and performed analysis for certain days involving certain disturbances. Through this effort, we have validated the proposed delay propagation models under disruptive events.

Agent-based and phylogenetic analyses reveal how HIV-1 moves between risk groups: injecting drug users sustain the heterosexual epidemic in Latvia

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Graw, Frederik; Leitner, Thomas; Ribeiro, Ruy M.

2012-01-01

Injecting drug users (IDU) are a driving force for the spread of HIV-1 in Latvia and other Baltic States, accounting for a majority of cases. However, in recent years, heterosexual cases have increased disproportionately. It is unclear how the changes in incidence patterns in Latvia can be explained, and how important IDU are for the heterosexual sub-epidemic. We introduce a novel epidemic model and use phylogenetic analyses in parallel to examine the spread of HIV-1 in Latvia between 1987 and 2010. Using a hybrid framework with a mean-field description for the susceptible population and an agent-based model for the infecteds, we track infected individuals and follow transmission histories dynamically formed during the simulation. The agent-based simulations and the phylogenetic analysis show that more than half of the heterosexual transmissions in Latvia were caused by IDU, which sustain the heterosexual epidemic. Indeed, we find that heterosexual clusters are characterized by short transmission chains with up to 63% of the chains dying out after the first introduction. In the simulations, the distribution of transmission chain sizes follows a power law distribution, which is confirmed by the phylogenetic data. Our models indicate that frequent introductions reduced the extinction probability of an autonomously spreading heterosexual HIV-1 epidemic, which now has the potential to dominate the spread of the overall epidemic in the future. Furthermore, our model shows that social heterogeneity of the susceptible population can explain the shift in HIV-1 incidence in Latvia over the course of the epidemic. Thus, the decrease in IDU incidence may be due to local heterogeneities in transmission, rather than the implementation of control measures. Increases in susceptibles, through social or geographic movement of IDU, could lead to a boost in HIV-1 infections in this risk group. Targeting individuals that bridge social groups would help prevent further spread of the

Epidemics spreading in interconnected complex networks

International Nuclear Information System (INIS)

Wang, Y.; Xiao, G.

2012-01-01

We study epidemic spreading in two interconnected complex networks. It is found that in our model the epidemic threshold of the interconnected network is always lower than that in any of the two component networks. Detailed theoretical analysis is proposed which allows quick and accurate calculations of epidemic threshold and average outbreak/epidemic size. Theoretical analysis and simulation results show that, generally speaking, the epidemic size is not significantly affected by the inter-network correlation. In interdependent networks which can be viewed as a special case of interconnected networks, however, impacts of inter-network correlation on the epidemic threshold and outbreak size are more significant. -- Highlights: ► We study epidemic spreading in two interconnected complex networks. ► The epidemic threshold is lower than that in any of the two networks. And Interconnection correlation has impacts on threshold and average outbreak size. ► Detailed theoretical analysis is proposed which allows quick and accurate calculations of epidemic threshold and average outbreak/epidemic size. ► We demonstrated and proved that Interconnection correlation does not affect epidemic size significantly. ► In interdependent networks, impacts of inter-network correlation on the epidemic threshold and outbreak size are more significant.

Epidemics spreading in interconnected complex networks

Energy Technology Data Exchange (ETDEWEB)

Wang, Y. [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore); Institute of High Performance Computing, Agency for Science, Technology and Research (A-STAR), Singapore 138632 (Singapore); Xiao, G., E-mail: egxxiao@ntu.edu.sg [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore)

2012-09-03

We study epidemic spreading in two interconnected complex networks. It is found that in our model the epidemic threshold of the interconnected network is always lower than that in any of the two component networks. Detailed theoretical analysis is proposed which allows quick and accurate calculations of epidemic threshold and average outbreak/epidemic size. Theoretical analysis and simulation results show that, generally speaking, the epidemic size is not significantly affected by the inter-network correlation. In interdependent networks which can be viewed as a special case of interconnected networks, however, impacts of inter-network correlation on the epidemic threshold and outbreak size are more significant. -- Highlights: ► We study epidemic spreading in two interconnected complex networks. ► The epidemic threshold is lower than that in any of the two networks. And Interconnection correlation has impacts on threshold and average outbreak size. ► Detailed theoretical analysis is proposed which allows quick and accurate calculations of epidemic threshold and average outbreak/epidemic size. ► We demonstrated and proved that Interconnection correlation does not affect epidemic size significantly. ► In interdependent networks, impacts of inter-network correlation on the epidemic threshold and outbreak size are more significant.

Connecting the obesity and the narcissism epidemics.

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Lemaitre, Bruno

2016-10-01

Obesity and metabolic syndromes are major threats to health in both developed and developing countries. This opinion article is a holistic attempt to understand the obesity epidemic, by connecting it to the widespread narcissism in society. The narcissism epidemic refers to an increased prevalence of status-striving individualism and a decreased sense of community, observed in Westerns populations and spreading worldwide. Based on social personality and evolutionary psychology approaches, I speculate that this rise of narcissism underlies a steep social hierarchy resulting in increase of social stress. This social stress markedly affects individuals who are sensitive to social hierarchy dominance due to their personality, yet are relegated at a lower social position. I speculate that over-eating is one major mechanism for coping with this stress, and discuss the possibility that visceral fat may constitute an adaptive behaviour to the lower social hierarchy position, which is perceived as unjust. Connecting the prevalence of obesity to the narcissism epidemic allows for a more thorough examination of factors, which contribute to obesity, which includes early difficult childhood experience, lower rank, and the overall competitive framework of the society. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

How heterogeneous susceptibility and recovery rates affect the spread of epidemics on networks

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Wei Gou

2017-08-01

Full Text Available In this paper, an extended heterogeneous SIR model is proposed, which generalizes the heterogeneous mean-field theory. Different from the traditional heterogeneous mean-field model only taking into account the heterogeneity of degree, our model considers not only the heterogeneity of degree but also the heterogeneity of susceptibility and recovery rates. Then, we analytically study the basic reproductive number and the final epidemic size. Combining with numerical simulations, it is found that the basic reproductive number depends on the mean of distributions of susceptibility and disease course when both of them are independent. If the mean of these two distributions is identical, increasing the variance of susceptibility may block the spread of epidemics, while the corresponding increase in the variance of disease course has little effect on the final epidemic size. It is also shown that positive correlations between individual susceptibility, course of disease and the square of degree make the population more vulnerable to epidemic and avail to the epidemic prevalence, whereas the negative correlations make the population less vulnerable and impede the epidemic prevalence. Keywords: Networks, Heterogeneity, Susceptibility, Recovery rates, Correlation, The basic reproductive number, The final epidemic size

Epidemic mitigation via awareness propagation in communication networks: the role of time scales

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Wang, Huijuan; Chen, Chuyi; Qu, Bo; Li, Daqing; Havlin, Shlomo

2017-07-01

The participation of individuals in multi-layer networks allows for feedback between network layers, opening new possibilities to mitigate epidemic spreading. For instance, the spread of a biological disease such as Ebola in a physical contact network may trigger the propagation of the information related to this disease in a communication network, e.g. an online social network. The information propagated in the communication network may increase the awareness of some individuals, resulting in them avoiding contact with their infected neighbors in the physical contact network, which might protect the population from the infection. In this work, we aim to understand how the time scale γ of the information propagation (speed that information is spread and forgotten) in the communication network relative to that of the epidemic spread (speed that an epidemic is spread and cured) in the physical contact network influences such mitigation using awareness information. We begin by proposing a model of the interaction between information propagation and epidemic spread, taking into account the relative time scale γ. We analytically derive the average fraction of infected nodes in the meta-stable state for this model (i) by developing an individual-based mean-field approximation (IBMFA) method and (ii) by extending the microscopic Markov chain approach (MMCA). We show that when the time scale γ of the information spread relative to the epidemic spread is large, our IBMFA approximation is better compared to MMCA near the epidemic threshold, whereas MMCA performs better when the prevalence of the epidemic is high. Furthermore, we find that an optimal mitigation exists that leads to a minimal fraction of infected nodes. The optimal mitigation is achieved at a non-trivial relative time scale γ, which depends on the rate at which an infected individual becomes aware. Contrary to our intuition, information spread too fast in the communication network could reduce the

Modeling the 2014 Ebola Virus Epidemic - Agent-Based Simulations, Temporal Analysis and Future Predictions for Liberia and Sierra Leone.

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Siettos, Constantinos; Anastassopoulou, Cleo; Russo, Lucia; Grigoras, Christos; Mylonakis, Eleftherios

2015-03-09

We developed an agent-based model to investigate the epidemic dynamics of Ebola virus disease (EVD) in Liberia and Sierra Leone from May 27 to December 21, 2014. The dynamics of the agent-based simulator evolve on small-world transmission networks of sizes equal to the population of each country, with adjustable densities to account for the effects of public health intervention policies and individual behavioral responses to the evolving epidemic. Based on time series of the official case counts from the World Health Organization (WHO), we provide estimates for key epidemiological variables by employing the so-called Equation-Free approach. The underlying transmission networks were characterized by rather random structures in the two countries with densities decreasing by ~19% from the early (May 27-early August) to the last period (mid October-December 21). Our estimates for the values of key epidemiological variables, such as the mean time to death, recovery and the case fatality rate, are very close to the ones reported by the WHO Ebola response team during the early period of the epidemic (until September 14) that were calculated based on clinical data. Specifically, regarding the effective reproductive number Re, our analysis suggests that until mid October, Re was above 2.3 in both countries; from mid October to December 21, Re dropped well below unity in Liberia, indicating a saturation of the epidemic, while in Sierra Leone it was around 1.9, indicating an ongoing epidemic. Accordingly, a ten-week projection from December 21 estimated that the epidemic will fade out in Liberia in early March; in contrast, our results flashed a note of caution for Sierra Leone since the cumulative number of cases could reach as high as 18,000, and the number of deaths might exceed 5,000, by early March 2015. However, by processing the reported data of the very last period (December 21, 2014-January 18, 2015), we obtained more optimistic estimates indicative of a remission of

Epidemics in interconnected small-world networks

NARCIS (Netherlands)

Liu, M.; Li, D.; Qin, P.; Liu, C.; Wang, H.; Wang, F.

2015-01-01

Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks

Keeping the Community Posted: Lesbian, Gay, Bisexual, and Transgender Blogs and the Tobacco Epidemic.

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Lee, Joseph G L

2014-06-01

Lesbian, gay, bisexual, and transgender (LGBT) people are more likely to use tobacco products than heterosexual people. This results in disproportionate death and disability for LGBT communities. Yet, addressing the tobacco epidemic is generally low on the agenda of LGBT community organizations, and LGBT individuals report lower levels of support for some evidence-based tobacco prevention and control policies than heterosexuals. Informed by agenda-setting theory, this study investigated coverage of the tobacco epidemic in LGBT news blogs. Sixteen blogs and 105 tobacco-related posts from 2003 to March 9, 2013, were identified, and a quantitative content analysis was conducted. Coverage of the tobacco epidemic was primarily concentrated in four blogs and focused on the epidemiology of the epidemic and on tobacco-related policies. Little coverage focused on the tobacco industry, addiction, or health effects. A substantial minority of coverage focused on socially conservative arguments comparing smoking to homosexuality as a lifestyle choice. Thirty-three organizations working on LGBT tobacco prevention and control were present in blog posts. LGBT news blogs have a potentially important and mostly untapped role in tobacco-related media advocacy. LGBT health advocates would do well to cultivate relationships with LGBT bloggers as well as include bloggers in dissemination and media strategy efforts.

Dynamics of epidemic diseases on a growing adaptive network.

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Demirel, Güven; Barter, Edmund; Gross, Thilo

2017-02-10

The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists.

Epidemic spreading on preferred degree adaptive networks.

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Jolad, Shivakumar; Liu, Wenjia; Schmittmann, B; Zia, R K P

2012-01-01

We study the standard SIS model of epidemic spreading on networks where individuals have a fluctuating number of connections around a preferred degree κ. Using very simple rules for forming such preferred degree networks, we find some unusual statistical properties not found in familiar Erdös-Rényi or scale free networks. By letting κ depend on the fraction of infected individuals, we model the behavioral changes in response to how the extent of the epidemic is perceived. In our models, the behavioral adaptations can be either 'blind' or 'selective'--depending on whether a node adapts by cutting or adding links to randomly chosen partners or selectively, based on the state of the partner. For a frozen preferred network, we find that the infection threshold follows the heterogeneous mean field result λ(c)/μ = / and the phase diagram matches the predictions of the annealed adjacency matrix (AAM) approach. With 'blind' adaptations, although the epidemic threshold remains unchanged, the infection level is substantially affected, depending on the details of the adaptation. The 'selective' adaptive SIS models are most interesting. Both the threshold and the level of infection changes, controlled not only by how the adaptations are implemented but also how often the nodes cut/add links (compared to the time scales of the epidemic spreading). A simple mean field theory is presented for the selective adaptations which capture the qualitative and some of the quantitative features of the infection phase diagram.

Modelling the dynamics of nonendemic epidemics

International Nuclear Information System (INIS)

Ramani, A.; Grammaticos, B.; Satsuma, J.

2009-01-01

We present two models for an epidemic where the individuals are infective over a fixed period of time and which never becomes endemic i.e., no infective individuals remain after the epidemic has run its course. The first model is based on a delay-difference scheme. We show that, as a function of the delay (which corresponds to the period of infectiveness) the percentage of non-infected population varies over a wide range. We present also a variant of our model where the recovery rate follows a Poisson law and obtain a discrete version of the SIR model. We estimate the percentage of non-infected population in the two models, show that they lead to almost the same values and present an explanation of this fact. The second model is based on the assumption that the infection is spread by carriers. Under the hypothesis that the carriers are relatively long-lived, and that the number of the infected ones is a relatively small fraction of the total population of potential carriers, we show that the model reduces to the same version of the discrete SIR obtained by our first model.

[Epidemics and pandemics in general practice. What can we learn from the swine flu (H1N1) and EHEC outbreak?].

Science.gov (United States)

Eisele, M; Hansen, H; Wagner, H-O; von Leitner, E; Pohontsch, N; Scherer, M

2014-06-01

As primary care givers with a coordinating function, general practitioners (GP) play a key role in dealing with epidemics and pandemics. As of yet, there are no studies in Germany describing the difficulties experienced by GPs in patient care during epidemics/pandemics. This study aimed at identifying the problem areas in GPs' patient care during the H1N1 and EHEC (enterohemorrhagic strain of Escherichia coli) outbreaks. With this information, recommendations for guaranteeing proper patient care during future epidemics/pandemics can be derived. In all, 12 qualitative, semi-structured, open guideline interviews with GPs in Hamburg and Lübeck were conducted, transcribed, and evaluated with qualitative content analysis. Five areas in ambulatory patient care were identified in which changes are needed from the primary care perspective: provision of information for GPs, workload, financing of epidemic-related measures, organization of the practices, care of those taken ill. The workload of GPs in particular can and should be reduced through successful, centralized information distribution during epidemics/pandemics. The GP's function as a coordinator should be supported and consolidated, in order to relieve the in-patient sector in cases of an epidemic/pandemic. Secured financing of epidemic-associated measures can help ensure patient care.

Can rewiring strategy control the epidemic spreading?

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Dong, Chao; Yin, Qiuju; Liu, Wenyang; Yan, Zhijun; Shi, Tianyu

2015-11-01

Relation existed in the social contact network can affect individuals' behaviors greatly. Considering the diversity of relation intimacy among network nodes, an epidemic propagation model is proposed by incorporating the link-breaking threshold, which is normally neglected in the rewiring strategy. The impact of rewiring strategy on the epidemic spreading in the weighted adaptive network is explored. The results show that the rewiring strategy cannot always control the epidemic prevalence, especially when the link-breaking threshold is low. Meanwhile, as well as strong links, weak links also play a significant role on epidemic spreading.

Untangling the Interplay between Epidemic Spread and Transmission Network Dynamics.

Directory of Open Access Journals (Sweden)

Christel Kamp

Full Text Available The epidemic spread of infectious diseases is ubiquitous and often has a considerable impact on public health and economic wealth. The large variability in the spatio-temporal patterns of epidemics prohibits simple interventions and requires a detailed analysis of each epidemic with respect to its infectious agent and the corresponding routes of transmission. To facilitate this analysis, we introduce a mathematical framework which links epidemic patterns to the topology and dynamics of the underlying transmission network. The evolution, both in disease prevalence and transmission network topology, is derived from a closed set of partial differential equations for infections without allowing for recovery. The predictions are in excellent agreement with complementarily conducted agent-based simulations. The capacity of this new method is demonstrated in several case studies on HIV epidemics in synthetic populations: it allows us to monitor the evolution of contact behavior among healthy and infected individuals and the contributions of different disease stages to the spreading of the epidemic. This gives both direction to and a test bed for targeted intervention strategies for epidemic control. In conclusion, this mathematical framework provides a capable toolbox for the analysis of epidemics from first principles. This allows for fast, in silico modeling--and manipulation--of epidemics and is especially powerful if complemented with adequate empirical data for parameterization.

Epidemic transmission on random mobile network with diverse infection periods

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Li, Kezan; Yu, Hong; Zeng, Zhaorong; Ding, Yong; Ma, Zhongjun

2015-05-01

The heterogeneity of individual susceptibility and infectivity and time-varying topological structure are two realistic factors when we study epidemics on complex networks. Current research results have shown that the heterogeneity of individual susceptibility and infectivity can increase the epidemic threshold in a random mobile dynamical network with the same infection period. In this paper, we will focus on random mobile dynamical networks with diverse infection periods due to people's different constitutions and external circumstances. Theoretical results indicate that the epidemic threshold of the random mobile network with diverse infection periods is larger than the counterpart with the same infection period. Moreover, the heterogeneity of individual susceptibility and infectivity can play a significant impact on disease transmission. In particular, the homogeneity of individuals will avail to the spreading of epidemics. Numerical examples verify further our theoretical results very well.

Epidemic spreading in time-varying community networks.

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Ren, Guangming; Wang, Xingyuan

2014-06-01

The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold qc. The epidemic will survive when q > qc and die when q epidemic spreading in complex networks with community structure.

The decline of the impetigo epidemic caused by the epidemic European fusidic acid-resistant impetigo clone: an 11.5-year population-based incidence study from a community in Western Norway.

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Rørtveit, Sverre; Skutlaberg, Dag Harald; Langeland, Nina; Rortveit, Guri

2014-12-01

From around the year 2000, Northern Europe experienced a rise in impetigo caused by Staphylococcus aureus resistant to fusidic acid. A single clone of S. aureus was found to be the bacterial pathogen involved in the impetigo outbreak in Norway, Sweden, the UK and Ireland, termed 'the epidemic European fusidic acid-resistant impetigo clone' (EEFIC). We have followed the incidence of impetigo during the years 2001-2012 based on all patients in general practice in the island community of Austevoll, Western Norway. We previously reported a marked decline of impetigo incidence in Austevoll, from 0.0260 cases per person-year in 2002 to 0.0038 in 2009. This article explores indications of an end to the impetigo epidemic caused by the EEFIC clone. All four general practitioners (GPs) in the community (mean population = 4400) were asked to diagnose impetigo in a uniform way and to take bacterial specimens from all impetigo cases. Phenotypic characteristics of specimen bacteria were determined for the whole period and molecular analyses were performed on isolates in the period 2008-2012. We observed a further decline in incidence of impetigo in Austevoll in the study period. The proportion of fusidic acid-resistant S. aureus isolates decreased during the period 2002-2012, with a mean of 80% in the epidemic years of 2002-2004, 55% in 2005-2009, and 6% in 2010-2012. In total, 44 S. aureus isolates from impetigo were subject to molecular analyses in the period 2008-2012, and 11 were found to be related to the EEFIC. All EEFIC isolates were found in 2008-2009, with no new isolates in 2010-2012. There is an apparent end to the impetigo epidemic related to the EEFIC in this population in Western Norway.

Bayesian projection of life expectancy accounting for the HIV/AIDS epidemic

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Jessica Godwin

2017-11-01

Full Text Available Background: While probabilistic projection methods for projecting life expectancy exist, few account for covariates related to life expectancy. Generalized HIV/AIDS epidemics have a large, immediate negative impact on the life expectancy in a country, but this impact can be mitigated by widespread use of antiretroviral therapy (ART. Thus, projection methods for countries with generalized HIV/AIDS epidemics could be improved by accounting for HIV prevalence, the future course of the epidemic, and ART coverage. Methods: We extend the current Bayesian probabilistic life expectancy projection methods of Raftery et al. (2013 to account for HIV prevalence and adult ART coverage in countries with generalized HIV/AIDS epidemics. Results: We evaluate our method using out-of-sample validation. We find that the proposed method performs better than the method that does not account for HIV prevalence or ART coverage for projections of life expectancy in countries with a generalized epidemic, while projections for countries without an epidemic remain essentially unchanged. Conclusions: In general, our projections show rapid recovery to pre-epidemic life expectancy levels in the presence of widespread ART coverage. After the initial life expectancy recovery, we project a steady rise in life expectancy until the end of the century. Contribution: We develop a simple Bayesian hierarchical model for long-term projections of life expectancy while accounting for HIV/AIDS prevalence and coverage of ART. The method produces well-calibrated projections for countries with generalized HIV/AIDS epidemics up to 2100 while having limited data demands.

Testing the hypothesis that treatment can eliminate HIV: a nationwide, population-based study of the Danish HIV epidemic in men who have sex with men.

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Okano, Justin T; Robbins, Danielle; Palk, Laurence; Gerstoft, Jan; Obel, Niels; Blower, Sally

2016-07-01

Worldwide, approximately 35 million individuals are infected with HIV; about 25 million of these live in sub-Saharan Africa. WHO proposes using treatment as prevention (TasP) to eliminate HIV. Treatment suppresses viral load, decreasing the probability an individual transmits HIV. The elimination threshold is one new HIV infection per 1000 individuals. Here, we test the hypothesis that TasP can substantially reduce epidemics and eliminate HIV. We estimate the impact of TasP, between 1996 and 2013, on the Danish HIV epidemic in men who have sex with men (MSM), an epidemic UNAIDS has identified as a priority for elimination. We use a CD4-staged Bayesian back-calculation approach to estimate incidence, and the hidden epidemic (the number of HIV-infected undiagnosed MSM). To develop the back-calculation model, we use data from an ongoing nationwide population-based study: the Danish HIV Cohort Study. Incidence, and the hidden epidemic, decreased substantially after treatment was introduced in 1996. By 2013, incidence was close to the elimination threshold: 1·4 (median, 95% Bayesian credible interval [BCI] 0·4-2·1) new HIV infections per 1000 MSM and there were only 617 (264-858) undiagnosed MSM. Decreasing incidence and increasing treatment coverage were highly correlated; a treatment threshold effect was apparent. Our study is the first to show that TasP can substantially reduce a country's HIV epidemic, and bring it close to elimination. However, we have shown the effectiveness of TasP under optimal conditions: very high treatment coverage, and exceptionally high (98%) viral suppression rate. Unless these extremely challenging conditions can be met in sub-Saharan Africa, the WHO's global elimination strategy is unlikely to succeed. National Institute of Allergy and Infectious Diseases. Copyright © 2016 Elsevier Ltd. All rights reserved.

Epidemic spreading on random surfer networks with infected avoidance strategy

International Nuclear Information System (INIS)

Feng Yun; Ding Li; Huang Yun-Han; Guan Zhi-Hong

2016-01-01

In this paper, we study epidemic spreading on random surfer networks with infected avoidance (IA) strategy. In particular, we consider that susceptible individuals’ moving direction angles are affected by the current location information received from infected individuals through a directed information network. The model is mainly analyzed by discrete-time numerical simulations. The results indicate that the IA strategy can restrain epidemic spreading effectively. However, when long-distance jumps of individuals exist, the IA strategy’s effectiveness on restraining epidemic spreading is heavily reduced. Finally, it is found that the influence of the noises from information transferring process on epidemic spreading is indistinctive. (paper)

Epidemic spread in bipartite network by considering risk awareness

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Han, She; Sun, Mei; Ampimah, Benjamin Chris; Han, Dun

2018-02-01

Human awareness plays an important role in the spread of infectious diseases and the control of propagation patterns. Exploring the interplay between human awareness and epidemic spreading is a topic that has been receiving increasing attention. Considering the fact, some well-known diseases only spread between different species we propose a theoretical analysis of the Susceptible-Infected-Susceptible (SIS) epidemic spread from the perspective of bipartite network and risk aversion. Using mean field theory, the epidemic threshold is calculated theoretically. Simulation results are consistent with the proposed analytic model. The results show that, the final infection density is negative linear with the value of individuals' risk awareness. Therefore, the epidemic spread could be effectively suppressed by improving individuals' risk awareness.

Epidemics in interconnected small-world networks.

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Liu, Meng; Li, Daqing; Qin, Pengju; Liu, Chaoran; Wang, Huijuan; Wang, Feilong

2015-01-01

Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks has rarely been considered. Here, we study the susceptible-infected-susceptible (SIS) model of epidemic spreading in a system comprising two interconnected small-world networks. We find that the epidemic threshold in such networks decreases when the rewiring probability of the component small-world networks increases. When the infection rate is low, the rewiring probability affects the global steady-state infection density, whereas when the infection rate is high, the infection density is insensitive to the rewiring probability. Moreover, epidemics in interconnected small-world networks are found to spread at different velocities that depend on the rewiring probability.

Epidemics in interconnected small-world networks.

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Meng Liu

Full Text Available Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks has rarely been considered. Here, we study the susceptible-infected-susceptible (SIS model of epidemic spreading in a system comprising two interconnected small-world networks. We find that the epidemic threshold in such networks decreases when the rewiring probability of the component small-world networks increases. When the infection rate is low, the rewiring probability affects the global steady-state infection density, whereas when the infection rate is high, the infection density is insensitive to the rewiring probability. Moreover, epidemics in interconnected small-world networks are found to spread at different velocities that depend on the rewiring probability.

On the probability of extinction of the Haiti cholera epidemic

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Bertuzzo, Enrico; Finger, Flavio; Mari, Lorenzo; Gatto, Marino; Rinaldo, Andrea

2014-05-01

Nearly 3 years after its appearance in Haiti, cholera has already exacted more than 8,200 deaths and 670,000 reported cases and it is feared to become endemic. However, no clear evidence of a stable environmental reservoir of pathogenic Vibrio cholerae, the infective agent of the disease, has emerged so far, suggesting that the transmission cycle of the disease is being maintained by bacteria freshly shed by infected individuals. Thus in principle cholera could possibly be eradicated from Haiti. Here, we develop a framework for the estimation of the probability of extinction of the epidemic based on current epidemiological dynamics and health-care practice. Cholera spreading is modelled by an individual-based spatially-explicit stochastic model that accounts for the dynamics of susceptible, infected and recovered individuals hosted in different local communities connected through hydrologic and human mobility networks. Our results indicate that the probability that the epidemic goes extinct before the end of 2016 is of the order of 1%. This low probability of extinction highlights the need for more targeted and effective interventions to possibly stop cholera in Haiti.

Risk perceptions of MSF healthcare workers on the recent Ebola epidemic in West Africa

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S. Sridhar

2016-07-01

Full Text Available Healthcare workers (HCW in general are considered to be at high risk during epidemics. Their training for Ebola provided by Médecins sans frontières (MSF is presently based on imparting factual information, which does not necessarily translate into knowledge or appropriate practices. We aimed to understand the importance of risk perception during training. A total of 130 MSF-trained HCW traveling to Africa during the Ebola epidemic of 2014–2015 participated in this longitudinal cohort study. Their baseline knowledge was good but did not significantly increase after training except for minor symptoms, case fatality rate and wearing personal protective equipment as a preventive measure. Additionally, they underestimated their likelihood for contracting Ebola compared to their colleagues of same age and sex, and despite their high-risk status, they showed little concern about contracting Ebola during their mission. Our findings suggest that the use of individualized risk feedback during training in appraising erroneous perceptions will increase adherence to preventive measures.

Epidemic spreading between two coupled subpopulations with inner structures

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Ruan, Zhongyuan; Tang, Ming; Gu, Changgui; Xu, Jinshan

2017-10-01

The structure of underlying contact network and the mobility of agents are two decisive factors for epidemic spreading in reality. Here, we study a model consisting of two coupled subpopulations with intra-structures that emphasizes both the contact structure and the recurrent mobility pattern of individuals simultaneously. We show that the coupling of the two subpopulations (via interconnections between them and round trips of individuals) makes the epidemic threshold in each subnetwork to be the same. Moreover, we find that the interconnection probability between two subpopulations and the travel rate are important factors for spreading dynamics. In particular, as a function of interconnection probability, the epidemic threshold in each subpopulation decreases monotonously, which enhances the risks of an epidemic. While the epidemic threshold displays a non-monotonic variation as travel rate increases. Moreover, the asymptotic infected density as a function of travel rate in each subpopulation behaves differently depending on the interconnection probability.

The Role of Node Heterogeneity in the Coupled Spreading of Epidemics and Awareness.

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Guo, Quantong; Lei, Yanjun; Xia, Chengyi; Guo, Lu; Jiang, Xin; Zheng, Zhiming

2016-01-01

Exploring the interplay between information spreading and epidemic spreading is a topic that has been receiving increasing attention. As an efficient means of depicting the spreading of information, which manifests as a cascade phenomenon, awareness cascading is utilized to investigate this coupled transmission. Because in reality, different individuals facing the same epidemic will exhibit distinct behaviors according to their own experiences and attributes, it is important for us to consider the heterogeneity of individuals. Consequently, we propose a heterogeneous spreading model. To describe the heterogeneity, two of the most important but radically different methods for this purpose, the degree and k-core measures, are studied in this paper through three models based on different assumptions. Adopting a Markov chain approach, we succeed in predicting the epidemic threshold trend. Furthermore, we find that when the k-core measure is used to classify individuals, the spreading process is robust to these models, meaning that regardless of the model used, the spreading process is nearly identical at the macroscopic level. In addition, the k-core measure leads to a much larger final epidemic size than the degree measure. These results are cross-checked through numerous simulations, not only of a synthetic network but also of a real multiplex network. The presented findings provide a better understanding of k-core individuals and reveal the importance of considering network structure when investigating various dynamic processes.

[A prognostic model of a cholera epidemic].

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Boev, B V; Bondarenko, V M; Prokop'eva, N V; San Román, R T; Raygoza-Anaya, M; García de Alba, R

1994-01-01

A new model for the prognostication of cholera epidemic on the territory of a large city is proposed. This model reflects the characteristic feature of contacting infection by sensitive individuals due to the preservation of Vibrio cholerae in their water habitat. The mathematical model of the epidemic quantitatively reflects the processes of the spread of infection by kinetic equations describing the interaction of the streams of infected persons, the causative agents and susceptible persons. The functions and parameters of the model are linked with the distribution of individuals according to the duration of the incubation period and infectious process, as well as the period of asymptomatic carrier state. The computer realization of the model by means of IBM PC/AT made it possible to study the cholera epidemic which took place in Mexico in 1833. The verified model of the cholera epidemic was used for the prognostication of the possible spread of this infection in Guadalajara, taking into account changes in the epidemiological situation and the size of the population, as well as improvements in sanitary and hygienic conditions, in the city.

Epidemic spreading in time-varying community networks

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Ren, Guangming, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [School of Electronic and Information, Guangdong Polytechnic Normal University, Guangzhou 510665 (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xingyuan, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China)

2014-06-15

The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q{sub c}. The epidemic will survive when q > q{sub c} and die when q < q{sub c}. These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure.

Epidemic spreading in time-varying community networks

International Nuclear Information System (INIS)

Ren, Guangming; Wang, Xingyuan

2014-01-01

The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q c . The epidemic will survive when q > q c and die when q  c . These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure

Epidemics in partially overlapped multiplex networks.

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Camila Buono

Full Text Available Many real networks exhibit a layered structure in which links in each layer reflect the function of nodes on different environments. These multiple types of links are usually represented by a multiplex network in which each layer has a different topology. In real-world networks, however, not all nodes are present on every layer. To generate a more realistic scenario, we use a generalized multiplex network and assume that only a fraction [Formula: see text] of the nodes are shared by the layers. We develop a theoretical framework for a branching process to describe the spread of an epidemic on these partially overlapped multiplex networks. This allows us to obtain the fraction of infected individuals as a function of the effective probability that the disease will be transmitted [Formula: see text]. We also theoretically determine the dependence of the epidemic threshold on the fraction [Formula: see text] of shared nodes in a system composed of two layers. We find that in the limit of [Formula: see text] the threshold is dominated by the layer with the smaller isolated threshold. Although a system of two completely isolated networks is nearly indistinguishable from a system of two networks that share just a few nodes, we find that the presence of these few shared nodes causes the epidemic threshold of the isolated network with the lower propagating capacity to change discontinuously and to acquire the threshold of the other network.

Global stability results for a generalized Lotka-Volterra system with distributed delays. Applications to predator-prey and to epidemic systems.

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Beretta, E; Capasso, V; Rinaldi, F

1988-01-01

The paper contains an extension of the general ODE system proposed in previous papers by the same authors, to include distributed time delays in the interaction terms. The new system describes a large class of Lotka-Volterra like population models and epidemic models with continuous time delays. Sufficient conditions for the boundedness of solutions and for the global asymptotic stability of nontrivial equilibrium solutions are given. A detailed analysis of the epidemic system is given with respect to the conditions for global stability. For a relevant subclass of these systems an existence criterion for steady states is also given.

Epidemics on interconnected networks

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Dickison, Mark; Havlin, S.; Stanley, H. E.

2012-06-01

Populations are seldom completely isolated from their environment. Individuals in a particular geographic or social region may be considered a distinct network due to strong local ties but will also interact with individuals in other networks. We study the susceptible-infected-recovered process on interconnected network systems and find two distinct regimes. In strongly coupled network systems, epidemics occur simultaneously across the entire system at a critical infection strength βc, below which the disease does not spread. In contrast, in weakly coupled network systems, a mixed phase exists below βc of the coupled network system, where an epidemic occurs in one network but does not spread to the coupled network. We derive an expression for the network and disease parameters that allow this mixed phase and verify it numerically. Public health implications of communities comprising these two classes of network systems are also mentioned.

Epidemic as a natural process.

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Koivu-Jolma, Mikko; Annila, Arto

2018-05-01

Mathematical epidemiology is a well-recognized discipline to model infectious diseases. It also provides guidance for public health officials to limit outbreaks. Nevertheless, epidemics take societies by surprise every now and then, for example, when the Ebola virus epidemic raged seemingly unrestrained in Western Africa. We provide insight to this capricious character of nature by describing the epidemic as a natural process, i.e., a phenomenon governed by thermodynamics. Our account, based on statistical mechanics of open systems, clarifies that it is impossible to predict accurately epidemic courses because everything depends on everything else. Nonetheless, the thermodynamic theory yields a comprehensive and analytical view of the epidemic. The tenet subsumes various processes in a scale-free manner from the molecular to the societal levels. The holistic view accentuates overarching procedures in arresting and eradicating epidemics. Copyright © 2018 Elsevier Inc. All rights reserved.

Can epidemics be non-communicable?

DEFF Research Database (Denmark)

Seeberg, Jens; Meinert, Lotte

2015-01-01

This article argues that the concept of communicability that is central to the distinction between communicable diseases (CDs) and noncommunicable diseases (NCDs) is poorly conceptualized. The epidemic spread of NCDs such as diabetes, depression, and eating disorders demonstrates...... that they are communicable, even if they are not infectious. We need to more critically explore how they might be communicable in specific environments. All diseases with epidemic potential, we argue, should be assumed to be commun icable in a broader sense, and that the underlying medical distinction between infectious...... and noninfectious diseases confuses our understanding of NCD epidemics when these categories are treated as synonymous with ‘communicable’ and ‘noncommunicable’ diseases, respectively. The dominant role accorded to the concept of ‘lifestyle’, with its focus on individual responsibility, is part of the problem...

Addressing Future Epidemics: Historical Human Rights Lessons from the AIDS Pandemic

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Ambar Mehta

2016-05-01

Full Text Available Introduction: The Ebola epidemic in West Africa sparked many ethical and polarizing public health questions on how to adequately control transmission of the virus. These deliberations had and will continue to influence patients, healthcare workers, public perceptions of disease, and governmental responses. Such extensive and potential ramifications warranted an analysis of prior epidemics to sufficiently inform policy makers and prepare them and other authorities for future epidemics. We analyzed how the general public, medical institutions, federal government, and patients themselves responded during the early stages of the AIDS pandemic in two different countries and cultures, the United States and India. Discussion: Our analysis identified four key findings pertaining to the human rights of patients and healthcare workers and to the crucial roles of the government and medical community. The first demands that authoritative officials acknowledge the presence of high-risk behaviors and properly educate the public without stigmatizing groups of individuals. For this task, the medical community and federal government must form and display to the public a respectful and collaborative partnership towards battling the epidemic. These two synergistic endeavors will then allow appropriate officials to implement effective, yet civil, interventions for limiting transmission. Finally, the same officials must ensure that their interventions maintain the human rights of high-risk populations and of healthcare workers. Conclusions: Applying these findings to future epidemics of infectious diseases can aid policy makers in navigating complicated ethical and public health questions, and help prevent them from repeating past mistakes in handling epidemics.

Heterogeneity of the HIV epidemic in the general population of Karnataka state, south India

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Banandur Pradeep

2011-12-01

Full Text Available Abstract Background In the context of AVAHAN, the India AIDS Initiative of the Bill & Melinda Gates Foundation, general population surveys (GPS were carried out between 2006 and 2008 in Belgaum (northern, Bellary (mid-state and Mysore (southern districts of Karnataka state, south India. Data from these three surveys were analysed to understand heterogeneity in HIV risk. Methods Outcome variables were the prevalence of HIV and sexually transmitted infections (STIs. Independent variables included age, district, place of residence, along with socio-demographic, medical and behavioural characteristics. Multivariate logistic regression was undertaken to identify characteristics associated with HIV and differences between districts, incorporating survey statistics to consider weights and cluster effects. Results The participation rate was 79.0% for the interview and 72.5% for providing a blood or urine sample that was tested for HIV. Belgaum had the highest overall HIV (1.43% and Herpes simplex type-2 (HSV-2 (16.93% prevalence, and the lowest prevalence of curable STIs. In Belgaum, the HIV epidemic is predominantly rural, and among women. In Bellary, the epidemic is predominantly in urban areas and among men, and HIV prevalence was 1.18%. Mysore had the lowest prevalence of HIV (0.80% and HSV-2 (10.89% and the highest prevalence of curable STIs. Higher HIV prevalence among men was associated with increasing age (p25-29years=11.22,95%CI:1.42-88.74, AOR30-34years=13.13,95%CI:1.67-103.19 and AOR35-39years=11.33,95%CI:1.32-96.83, having more than one lifetime sexual partner (AOR=4.61,95%CI:1.26-16.91 and having ever used a condom (AOR=3.32,95%CI:1.38-7.99. Having a dissolved marriage (being widowed/divorced/separated was the strongest predictor (AOR=10.98,95%CI: 5.35-22.57 of HIV among women. Being a muslim woman was associated with lower HIV prevalence (AOR=0.27,95%CI:0.08-0.87. Conclusion The HIV epidemic in Karnataka shows considerable heterogeneity

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

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López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

2014-04-12

The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the

Analytical models approximating individual processes: a validation method.

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Favier, C; Degallier, N; Menkès, C E

2010-12-01

Upscaling population models from fine to coarse resolutions, in space, time and/or level of description, allows the derivation of fast and tractable models based on a thorough knowledge of individual processes. The validity of such approximations is generally tested only on a limited range of parameter sets. A more general validation test, over a range of parameters, is proposed; this would estimate the error induced by the approximation, using the original model's stochastic variability as a reference. This method is illustrated by three examples taken from the field of epidemics transmitted by vectors that bite in a temporally cyclical pattern, that illustrate the use of the method: to estimate if an approximation over- or under-fits the original model; to invalidate an approximation; to rank possible approximations for their qualities. As a result, the application of the validation method to this field emphasizes the need to account for the vectors' biology in epidemic prediction models and to validate these against finer scale models. Copyright © 2010 Elsevier Inc. All rights reserved.

Epidemic spreading in localized environments with recurrent mobility patterns

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Granell, Clara; Mucha, Peter J.

2018-05-01

The spreading of epidemics is very much determined by the structure of the contact network, which may be impacted by the mobility dynamics of the individuals themselves. In confined scenarios where a small, closed population spends most of its time in localized environments and has easily identifiable mobility patterns—such as workplaces, university campuses, or schools—it is of critical importance to identify the factors controlling the rate of disease spread. Here, we present a discrete-time, metapopulation-based model to describe the transmission of susceptible-infected-susceptible-like diseases that take place in confined scenarios where the mobilities of the individuals are not random but, rather, follow clear recurrent travel patterns. This model allows analytical determination of the onset of epidemics, as well as the ability to discern which contact structures are most suited to prevent the infection to spread. It thereby determines whether common prevention mechanisms, as isolation, are worth implementing in such a scenario and their expected impact.

Parasite transmission in social interacting hosts: Monogenean epidemics in guppies

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Johnson, Mirelle B.; Lafferty, Kevin D.; van Oosterhout, Cock; Cable, Joanne

2011-01-01

Background Infection incidence increases with the average number of contacts between susceptible and infected individuals. Contact rates are normally assumed to increase linearly with host density. However, social species seek out each other at low density and saturate their contact rates at high densities. Although predicting epidemic behaviour requires knowing how contact rates scale with host density, few empirical studies have investigated the effect of host density. Also, most theory assumes each host has an equal probability of transmitting parasites, even though individual parasite load and infection duration can vary. To our knowledge, the relative importance of characteristics of the primary infected host vs. the susceptible population has never been tested experimentally. Methodology/Principal Findings Here, we examine epidemics using a common ectoparasite, Gyrodactylus turnbulli infecting its guppy host (Poecilia reticulata). Hosts were maintained at different densities (3, 6, 12 and 24 fish in 40 L aquaria), and we monitored gyrodactylids both at a population and individual host level. Although parasite population size increased with host density, the probability of an epidemic did not. Epidemics were more likely when the primary infected fish had a high mean intensity and duration of infection. Epidemics only occurred if the primary infected host experienced more than 23 worm days. Female guppies contracted infections sooner than males, probably because females have a higher propensity for shoaling. Conclusions/Significance These findings suggest that in social hosts like guppies, the frequency of social contact largely governs disease epidemics independent of host density.

Epidemic spreading on random surfer networks with infected avoidance strategy

Science.gov (United States)

Feng, Yun; Ding, Li; Huang, Yun-Han; Guan, Zhi-Hong

2016-12-01

In this paper, we study epidemic spreading on random surfer networks with infected avoidance (IA) strategy. In particular, we consider that susceptible individuals’ moving direction angles are affected by the current location information received from infected individuals through a directed information network. The model is mainly analyzed by discrete-time numerical simulations. The results indicate that the IA strategy can restrain epidemic spreading effectively. However, when long-distance jumps of individuals exist, the IA strategy’s effectiveness on restraining epidemic spreading is heavily reduced. Finally, it is found that the influence of the noises from information transferring process on epidemic spreading is indistinctive. Project supported in part by the National Natural Science Foundation of China (Grant Nos. 61403284, 61272114, 61673303, and 61672112) and the Marine Renewable Energy Special Fund Project of the State Oceanic Administration of China (Grant No. GHME2013JS01).

Abia State HIV epidemic and response: challenges and prospects.

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Onyeonoro, Ugochukwu Uchenna; Emelumadu, Obiageli Fidelia; Nwamoh, Uche Ngozi; Ukegbu, Andrew Ugwunna; Okafor, Godwin Oc

2014-11-13

Since the first seroprevalence survey in 1999, the HIV prevalence in Abia State has increased from 1.8% to 7.3% in 2010. The state is currently experiencing a generalized epidemic, with most transmission occurring through heterosexual low-risk sex. Drivers of the epidemic include low knowledge of HIV prevention, low risk perception, predominantly male factor-driven risky sexual behavior, and low condom use. This study reviewed the state HIV epidemic trend in relation to response, sought to identify the gaps between the epidemic and response, and recommended measures to strengthen the state response.

Beyond network structure: How heterogeneous susceptibility modulates the spread of epidemics.

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Smilkov, Daniel; Hidalgo, Cesar A; Kocarev, Ljupco

2014-04-25

The compartmental models used to study epidemic spreading often assume the same susceptibility for all individuals, and are therefore, agnostic about the effects that differences in susceptibility can have on epidemic spreading. Here we show that-for the SIS model-differential susceptibility can make networks more vulnerable to the spread of diseases when the correlation between a node's degree and susceptibility are positive, and less vulnerable when this correlation is negative. Moreover, we show that networks become more likely to contain a pocket of infection when individuals are more likely to connect with others that have similar susceptibility (the network is segregated). These results show that the failure to include differential susceptibility to epidemic models can lead to a systematic over/under estimation of fundamental epidemic parameters when the structure of the networks is not independent from the susceptibility of the nodes or when there are correlations between the susceptibility of connected individuals.

Epidemic processes in complex networks

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Pastor-Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet; Vespignani, Alessandro

2015-07-01

In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.

Travelling Wave Solutions in Multigroup Age-Structured Epidemic Models

Science.gov (United States)

Ducrot, Arnaut; Magal, Pierre; Ruan, Shigui

2010-01-01

Age-structured epidemic models have been used to describe either the age of individuals or the age of infection of certain diseases and to determine how these characteristics affect the outcomes and consequences of epidemiological processes. Most results on age-structured epidemic models focus on the existence, uniqueness, and convergence to disease equilibria of solutions. In this paper we investigate the existence of travelling wave solutions in a deterministic age-structured model describing the circulation of a disease within a population of multigroups. Individuals of each group are able to move with a random walk which is modelled by the classical Fickian diffusion and are classified into two subclasses, susceptible and infective. A susceptible individual in a given group can be crisscross infected by direct contact with infective individuals of possibly any group. This process of transmission can depend upon the age of the disease of infected individuals. The goal of this paper is to provide sufficient conditions that ensure the existence of travelling wave solutions for the age-structured epidemic model. The case of two population groups is numerically investigated which applies to the crisscross transmission of feline immunodeficiency virus (FIV) and some sexual transmission diseases.

The SIS Model of Epidemic Spreading in a Hierarchical Social Network

International Nuclear Information System (INIS)

Grabowski, A.; Kosinski, R.A.

2005-01-01

The phenomenon of epidemic spreading in a population with a hierarchical structure of interpersonal interactions is described and investigated numerically. The SIS model with temporal immunity to a disease and a time of incubation is used. In our model spatial localization of individuals belonging to different social groups, effectiveness of different interpersonal interactions and the mobility of a contemporary community are taken into account. The structure of interpersonal connections is based on a scale-free network. The influence of the structure of the social network on typical relations characterizing the spreading process, like a range of epidemic and epidemic curves, is discussed. The probability that endemic state occurs is also calculated. Surprisingly it occurs, that less contagious diseases has greater chance to survive. The influence of preventive vaccinations on the spreading process is investigated and critical range of vaccinations that is sufficient for the suppression of an epidemic is calculated. Our results of numerical calculations are compared with the solutions of the master equation for the spreading process, and good agreement is found. (author)

A spatially explicit model for the future progression of the current Haiti cholera epidemic

Science.gov (United States)

Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.

2011-12-01

As a major cholera epidemic progresses in Haiti, and the figures of the infection, up to July 2011, climb to 385,000 cases and 5,800 deaths, the development of general models to track and predict the evolution of the outbreak, so as to guide the allocation of medical supplies and staff, is gaining notable urgency. We propose here a spatially explicit epidemic model that accounts for the dynamics of susceptible and infected individuals as well as the redistribution of textit{Vibrio cholera}, the causative agent of the disease, among different human communities. In particular, we model two spreading pathways: the advection of pathogens through hydrologic connections and the dissemination due to human mobility described by means of a gravity-like model. To this end the country has been divided into hydrologic units based on drainage directions derived from a digital terrain model. Moreover the population of each unit has been estimated from census data downscaled to 1 km x 1 km resolution via remotely sensed geomorphological information (LandScan texttrademark project). The model directly account for the role of rainfall patterns in driving the seasonality of cholera outbreaks. The two main outbreaks in fact occurred during the rainy seasons (October and May) when extensive floodings severely worsened the sanitation conditions and, in turn, raised the risk of infection. The model capability to reproduce the spatiotemporal features of the epidemic up to date grants robustness to the foreseen future development. In this context, the duration of acquired immunity, a hotly debated topic in the scientific community, emerges as a controlling factor for progression of the epidemic in the near future. The framework presented here can straightforwardly be used to evaluate the effectiveness of alternative intervention strategies like mass vaccinations, clean water supply and educational campaigns, thus emerging as an essential component of the control of future cholera

Epidemic impacts of a community empowerment intervention for HIV prevention among female sex workers in generalized and concentrated epidemics.

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Wirtz, Andrea L; Pretorius, Carel; Beyrer, Chris; Baral, Stefan; Decker, Michele R; Sherman, Susan G; Sweat, Michael; Poteat, Tonia; Butler, Jennifer; Oelrichs, Robert; Semini, Iris; Kerrigan, Deanna

2014-01-01

Sex workers have endured a high burden of HIV infection in and across HIV epidemics. A comprehensive, community empowerment-based HIV prevention intervention emphasizes sex worker organization and mobilization to address HIV risk and often includes community-led peer education, condom distribution, and other activities. Meta-analysis of such interventions suggests a potential 51% reduction in inconsistent condom use. Mathematical modeling exercises provide theoretical insight into potential impacts of the intervention on HIV incidence and burden in settings where interventions have not yet been implemented. We used a deterministic model, Goals, to project the impact on HIV infections when the community empowerment interventions were scaled up among female sex workers in Kenya, Thailand, Brazil, and Ukraine. Modeling scenarios included expansion of the comprehensive community empowerment-based HIV prevention intervention from baseline coverage over a 5-year period (5-65% in Kenya and Ukraine; 10-70% in Thailand and Brazil), while other interventions were held at baseline levels. A second exercise increased the intervention coverage simultaneously with equitable access to ART for sex workers. Impacts on HIV outcomes among sex workers and adults are observed from 2012-2016 and, compared to status quo when all interventions are held constant. Optimistic but feasible coverage (65%-70%) of the intervention demonstrated a range of impacts on HIV: 220 infections averted over 5 yrs. among sex workers in Thailand, 1,830 in Brazil, 2,220 in Ukraine, and 10,800 infections in Kenya. Impacts of the intervention for female sex workers extend to the adult population, cumulatively averting 730 infections in Thailand to 20,700 adult infections in Kenya. Impacts vary by country, influenced by HIV prevalence in risk groups, risk behaviors, intervention use, and population size. A community empowerment approach to HIV prevention and access to universal ART for female sex workers is a

[MANIFESTATIONS OF EPIDEMIC PROCESS AND TRANSMISSION ROUTES OF CAUSATIVE AGENT OF ENTEROVIRUS SEROUS MENINGITIS].

Science.gov (United States)

Sergevnin, V I; Tryasolobova, M A; Kudrevatykh, E V; Kuzovnikova, E Zh

2015-01-01

Study the manifestations of epidemic process and leading transmission routes of causative agents of enterovirus serous meningitis (SM) by results of laboratory studies and epidemiologic examination of epidemic nidi. During 2010 - 2014 a study for enterovirus was carried out in cerebrospinal fluid in 743 patients, hospitalized into medical organizations of Perm with primary diagnosis "serous meningitis", feces of 426 individuals, that had communicated with patients with SM of enterovirus etiology; 827 water samples from the distribution network, 295 water samples from open water and 57 washes from surface of vegetables and fruits. All the samples were studied in polymerase chain reaction, part--by a virological method. Epidemiologic examination of 350 epidemic nidi of SM was carried out. Enterovirus and (or) its RNA were detected in 62.0% of patients and 61.9% of individuals that had communicated with patients with enteroviris SM. ECHO 6 serotype enterovirus dominated among the causative agents. Maximum intensity of epidemic process of enterovirus SM, based on data from laboratory examination of patients, was detected in a group of organized pre-school and school age children during summer-autumn period. . Examination of epidemic nidi and laboratory control of environmental objects have shown that CV causative agent transmission factors are, in particular, unboiled water from decentralized sources (boreholes, wells, springs), water from open waters during bathing, as well as fresh vegetables, fruits, berries and meals produced from them. .

HIV status awareness, partnership dissolution and HIV transmission in generalized epidemics.

Science.gov (United States)

Reniers, Georges; Armbruster, Benjamin

2012-01-01

HIV status aware couples with at least one HIV positive partner are characterized by high separation and divorce rates. This phenomenon is often described as a corollary of couples HIV Testing and Counseling (HTC) that ought to be minimized. In this contribution, we demonstrate the implications of partnership dissolution in serodiscordant couples for the propagation of HIV. We develop a compartmental model to study epidemic outcomes of elevated partnership dissolution rates in serodiscordant couples and parameterize it with estimates from population-based data (Rakai, Uganda). Via its effect on partnership dissolution, every percentage point increase in HIV status awareness reduces HIV incidence in monogamous populations by 0.27 percent for women and 0.63 percent for men. These effects are even larger when the assumption of monogamy can be relaxed, but are moderated by other behavior changes (e.g., increased condom use) in HIV status aware serodiscordant partnerships. When these behavior changes are taken into account, each percentage point increase in HIV status awareness reduces HIV incidence by 0.13 and 0.32 percent for women and men, respectively (assuming monogamy). The partnership dissolution effect exists because it decreases the fraction of serodiscordant couples in the population and prolongs the time that individuals spend outside partnerships. Our model predicts that elevated partnership dissolution rates in HIV status aware serodiscordant couples reduce the spread of HIV. As a consequence, the full impact of couples HTC for HIV prevention is probably larger than recognized to date. Particularly high partnership dissolution rates in female positive serodiscordant couples contribute to the gender imbalance in HIV infections.

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

International Nuclear Information System (INIS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-01-01

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

Energy Technology Data Exchange (ETDEWEB)

Lu, Yunfan, E-mail: yunfanlu@yeah.net; Wang, Jun; Niu, Hongli

2015-06-12

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model.

Epidemic spreading in networks with nonrandom long-range interactions.

Science.gov (United States)

Estrada, Ernesto; Kalala-Mutombo, Franck; Valverde-Colmeiro, Alba

2011-09-01

An "infection," understood here in a very broad sense, can be propagated through the network of social contacts among individuals. These social contacts include both "close" contacts and "casual" encounters among individuals in transport, leisure, shopping, etc. Knowing the first through the study of the social networks is not a difficult task, but having a clear picture of the network of casual contacts is a very hard problem in a society of increasing mobility. Here we assume, on the basis of several pieces of empirical evidence, that the casual contacts between two individuals are a function of their social distance in the network of close contacts. Then, we assume that we know the network of close contacts and infer the casual encounters by means of nonrandom long-range (LR) interactions determined by the social proximity of the two individuals. This approach is then implemented in a susceptible-infected-susceptible (SIS) model accounting for the spread of infections in complex networks. A parameter called "conductance" controls the feasibility of those casual encounters. In a zero conductance network only contagion through close contacts is allowed. As the conductance increases the probability of having casual encounters also increases. We show here that as the conductance parameter increases, the rate of propagation increases dramatically and the infection is less likely to die out. This increment is particularly marked in networks with scale-free degree distributions, where infections easily become epidemics. Our model provides a general framework for studying epidemic spreading in networks with arbitrary topology with and without casual contacts accounted for by means of LR interactions.

A network-based meta-population approach to model Rift Valley fever epidemics.

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Xue, Ling; Scott, H Morgan; Cohnstaedt, Lee W; Scoglio, Caterina

2012-08-07

Rift Valley fever virus (RVFV) has been expanding its geographical distribution with important implications for both human and animal health. The emergence of Rift Valley fever (RVF) in the Middle East, and its continuing presence in many areas of Africa, has negatively impacted both medical and veterinary infrastructures and human morbidity, mortality, and economic endpoints. Furthermore, worldwide attention should be directed towards the broader infection dynamics of RVFV, because suitable host, vector and environmental conditions for additional epidemics likely exist on other continents; including Asia, Europe and the Americas. We propose a new compartmentalized model of RVF and the related ordinary differential equations to assess disease spread in both time and space; with the latter driven as a function of contact networks. Humans and livestock hosts and two species of vector mosquitoes are included in the model. The model is based on weighted contact networks, where nodes of the networks represent geographical regions and the weights represent the level of contact between regional pairings for each set of species. The inclusion of human, animal, and vector movements among regions is new to RVF modeling. The movement of the infected individuals is not only treated as a possibility, but also an actuality that can be incorporated into the model. We have tested, calibrated, and evaluated the model using data from the recent 2010 RVF outbreak in South Africa as a case study; mapping the epidemic spread within and among three South African provinces. An extensive set of simulation results shows the potential of the proposed approach for accurately modeling the RVF spreading process in additional regions of the world. The benefits of the proposed model are twofold: not only can the model differentiate the maximum number of infected individuals among different provinces, but also it can reproduce the different starting times of the outbreak in multiple locations

Evaluating Subcriticality during the Ebola Epidemic in West Africa.

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Wayne T A Enanoria

Full Text Available The 2014-2015 Ebola outbreak is the largest and most widespread to date. In order to estimate ongoing transmission in the affected countries, we estimated the weekly average number of secondary cases caused by one individual infected with Ebola throughout the infectious period for each affected West African country using a stochastic hidden Markov model fitted to case data from the World Health Organization. If the average number of infections caused by one Ebola infection is less than 1.0, the epidemic is subcritical and cannot sustain itself. The epidemics in Liberia and Sierra Leone have approached subcriticality at some point during the epidemic; the epidemic in Guinea is ongoing with no evidence that it is subcritical. Response efforts to control the epidemic should continue in order to eliminate Ebola cases in West Africa.

Epidemic dengue and dengue hemorrhagic fever at the Texas-Mexico border: results of a household-based seroepidemiologic survey, December 2005.

Science.gov (United States)

Ramos, Mary M; Mohammed, Hamish; Zielinski-Gutierrez, Emily; Hayden, Mary H; Lopez, Jose Luis Robles; Fournier, Marta; Trujillo, Alfredo Rodríguez; Burton, Roy; Brunkard, Joan M; Anaya-Lopez, Luis; Banicki, Allison Abell; Morales, Pablo Kuri; Smith, Brian; Muñoz, Jorge L; Waterman, Stephen H

2008-03-01

A dengue-2 epidemic causing dengue hemorrhagic fever (DHF) occurred in the contiguous border cities of Matamoros, Tamaulipas (Mexico), and Brownsville, TX, in 2005. In December, we conducted a household-based epidemiologic survey to determine the incidence and seroprevalence of dengue infection among Matamoros and Brownsville residents and to identify risk factors associated with infection. Antibodies to dengue were measured in 273 individuals. The estimated incidence of recent dengue infection was 32% and 4% among Matamoros and Brownsville participants, respectively. The estimated prevalence of past dengue infection was 77% and 39% among Matamoros and Brownsville participants, respectively. The Breteau index was 28 in Matamoros and 16 in Brownsville, reflecting an abundant winter population of Aedes mosquitoes. Discarded waste tires and buckets were the two largest categories of infested containers found in both cities. Our results underscore the risk for epidemic dengue and DHF in the Texas-Mexico border region.

Epidemic Survivability: Characterizing Networks Under Epidemic-like Failure Propagation Scenarios

DEFF Research Database (Denmark)

Manzano, Marc; Calle, Eusebi; Ripoll, Jordi

2013-01-01

Epidemics theory has been used in different contexts in order to describe the propagation of diseases, human interactions or natural phenomena. In computer science, virus spreading has been also characterized using epidemic models. Although in the past the use of epidemic models...... in telecommunication networks has not been extensively considered, nowadays, with the increasing computation capacity and complexity of operating systems of modern network devices (routers, switches, etc.), the study of possible epidemic-like failure scenarios must be taken into account. When epidemics occur......, such as in other multiple failure scenarios, identifying the level of vulnerability offered by a network is one of the main challenges. In this paper, we present epidemic survivability, a new network measure that describes the vulnerability of each node of a network under a specific epidemic intensity. Moreover...

Immunization strategy for epidemic spreading on multilayer networks

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Buono, C.; Braunstein, L. A.

2015-01-01

In many real-world complex systems, individuals have many kinds of interactions among them, suggesting that it is necessary to consider a layered-structure framework to model systems such as social interactions. This structure can be captured by multilayer networks and can have major effects on the spreading of process that occurs over them, such as epidemics. In this letter we study a targeted immunization strategy for epidemic spreading over a multilayer network. We apply the strategy in one of the layers and study its effect in all layers of the network disregarding degree-degree correlation among layers. We found that the targeted strategy is not as efficient as in isolated networks, due to the fact that in order to stop the spreading of the disease it is necessary to immunize more than 80% of the individuals. However, the size of the epidemic is drastically reduced in the layer where the immunization strategy is applied compared to the case with no mitigation strategy. Thus, the immunization strategy has a major effect on the layer were it is applied, but does not efficiently protect the individuals of other layers.

Impact of the infectious period on epidemics

Science.gov (United States)

Wilkinson, Robert R.; Sharkey, Kieran J.

2018-05-01

The duration of the infectious period is a crucial determinant of the ability of an infectious disease to spread. We consider an epidemic model that is network based and non-Markovian, containing classic Kermack-McKendrick, pairwise, message passing, and spatial models as special cases. For this model, we prove a monotonic relationship between the variability of the infectious period (with fixed mean) and the probability that the infection will reach any given subset of the population by any given time. For certain families of distributions, this result implies that epidemic severity is decreasing with respect to the variance of the infectious period. The striking importance of this relationship is demonstrated numerically. We then prove, with a fixed basic reproductive ratio (R0), a monotonic relationship between the variability of the posterior transmission probability (which is a function of the infectious period) and the probability that the infection will reach any given subset of the population by any given time. Thus again, even when R0 is fixed, variability of the infectious period tends to dampen the epidemic. Numerical results illustrate this but indicate the relationship is weaker. We then show how our results apply to message passing, pairwise, and Kermack-McKendrick epidemic models, even when they are not exactly consistent with the stochastic dynamics. For Poissonian contact processes, and arbitrarily distributed infectious periods, we demonstrate how systems of delay differential equations and ordinary differential equations can provide upper and lower bounds, respectively, for the probability that any given individual has been infected by any given time.

A simple model for behaviour change in epidemics

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Brauer Fred

2011-02-01

Full Text Available Abstract Background People change their behaviour during an epidemic. Infectious members of a population may reduce the number of contacts they make with other people because of the physical effects of their illness and possibly because of public health announcements asking them to do so in order to decrease the number of new infections, while susceptible members of the population may reduce the number of contacts they make in order to try to avoid becoming infected. Methods We consider a simple epidemic model in which susceptible and infectious members respond to a disease outbreak by reducing contacts by different fractions and analyze the effect of such contact reductions on the size of the epidemic. We assume constant fractional reductions, without attempting to consider the way in which susceptible members might respond to information about the epidemic. Results We are able to derive upper and lower bounds for the final size of an epidemic, both for simple and staged progression models. Conclusions The responses of uninfected and infected individuals in a disease outbreak are different, and this difference affects estimates of epidemic size.

Short-Term Dynamic and Local Epidemiological Trends in the South American HIV-1B Epidemic.

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Junqueira, Dennis Maletich; de Medeiros, Rubia Marília; Gräf, Tiago; Almeida, Sabrina Esteves de Matos

2016-01-01

The human displacement and sexual behavior are the main factors driving the HIV-1 pandemic to the current profile. The intrinsic structure of the HIV transmission among different individuals has valuable importance for the understanding of the epidemic and for the public health response. The aim of this study was to characterize the HIV-1 subtype B (HIV-1B) epidemic in South America through the identification of transmission links and infer trends about geographical patterns and median time of transmission between individuals. Sequences of the protease and reverse transcriptase coding regions from 4,810 individuals were selected from GenBank. Maximum likelihood phylogenies were inferred and submitted to ClusterPicker to identify transmission links. Bayesian analyses were applied only for clusters including ≥5 dated samples in order to estimate the median maximum inter-transmission interval. This study analyzed sequences sampled from 12 South American countries, from individuals of different exposure categories, under different antiretroviral profiles, and from a wide period of time (1989-2013). Continentally, Brazil, Argentina and Venezuela were revealed important sites for the spread of HIV-1B among countries inside South America. Of note, from all the clusters identified about 70% of the HIV-1B infections are primarily occurring among individuals living in the same geographic region. In addition, these transmissions seem to occur early after the infection of an individual, taking in average 2.39 years (95% CI 1.48-3.30) to succeed. Homosexual/Bisexual individuals transmit the virus as quickly as almost half time of that estimated for the general population sampled here. Public health services can be broadly benefitted from this kind of information whether to focus on specific programs of response to the epidemic whether as guiding of prevention campaigns to specific risk groups.

Short-Term Dynamic and Local Epidemiological Trends in the South American HIV-1B Epidemic.

Directory of Open Access Journals (Sweden)

Dennis Maletich Junqueira

Full Text Available The human displacement and sexual behavior are the main factors driving the HIV-1 pandemic to the current profile. The intrinsic structure of the HIV transmission among different individuals has valuable importance for the understanding of the epidemic and for the public health response. The aim of this study was to characterize the HIV-1 subtype B (HIV-1B epidemic in South America through the identification of transmission links and infer trends about geographical patterns and median time of transmission between individuals. Sequences of the protease and reverse transcriptase coding regions from 4,810 individuals were selected from GenBank. Maximum likelihood phylogenies were inferred and submitted to ClusterPicker to identify transmission links. Bayesian analyses were applied only for clusters including ≥5 dated samples in order to estimate the median maximum inter-transmission interval. This study analyzed sequences sampled from 12 South American countries, from individuals of different exposure categories, under different antiretroviral profiles, and from a wide period of time (1989-2013. Continentally, Brazil, Argentina and Venezuela were revealed important sites for the spread of HIV-1B among countries inside South America. Of note, from all the clusters identified about 70% of the HIV-1B infections are primarily occurring among individuals living in the same geographic region. In addition, these transmissions seem to occur early after the infection of an individual, taking in average 2.39 years (95% CI 1.48-3.30 to succeed. Homosexual/Bisexual individuals transmit the virus as quickly as almost half time of that estimated for the general population sampled here. Public health services can be broadly benefitted from this kind of information whether to focus on specific programs of response to the epidemic whether as guiding of prevention campaigns to specific risk groups.

Virulence evolution at the front line of spreading epidemics.

Science.gov (United States)

Griette, Quentin; Raoul, Gaël; Gandon, Sylvain

2015-11-01

Understanding and predicting the spatial spread of emerging pathogens is a major challenge for the public health management of infectious diseases. Theoretical epidemiology shows that the speed of an epidemic is governed by the life-history characteristics of the pathogen and its ability to disperse. Rapid evolution of these traits during the invasion may thus affect the speed of epidemics. Here we study the influence of virulence evolution on the spatial spread of an epidemic. At the edge of the invasion front, we show that more virulent and transmissible genotypes are expected to win the competition with other pathogens. Behind the front line, however, more prudent exploitation strategies outcompete virulent pathogens. Crucially, even when the presence of the virulent mutant is limited to the edge of the front, the invasion speed can be dramatically altered by pathogen evolution. We support our analysis with individual-based simulations and we discuss the additional effects of demographic stochasticity taking place at the front line on virulence evolution. We confirm that an increase of virulence can occur at the front, but only if the carrying capacity of the invading pathogen is large enough. These results are discussed in the light of recent empirical studies examining virulence evolution at the edge of spreading epidemics. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Model-Based Comprehensive Analysis of School Closure Policies for Mitigating Influenza Epidemics and Pandemics.

Science.gov (United States)

Fumanelli, Laura; Ajelli, Marco; Merler, Stefano; Ferguson, Neil M; Cauchemez, Simon

2016-01-01

School closure policies are among the non-pharmaceutical measures taken into consideration to mitigate influenza epidemics and pandemics spread. However, a systematic review of the effectiveness of alternative closure policies has yet to emerge. Here we perform a model-based analysis of four types of school closure, ranging from the nationwide closure of all schools at the same time to reactive gradual closure, starting from class-by-class, then grades and finally the whole school. We consider policies based on triggers that are feasible to monitor, such as school absenteeism and national ILI surveillance system. We found that, under specific constraints on the average number of weeks lost per student, reactive school-by-school, gradual, and county-wide closure give comparable outcomes in terms of optimal infection attack rate reduction, peak incidence reduction or peak delay. Optimal implementations generally require short closures of one week each; this duration is long enough to break the transmission chain without leading to unnecessarily long periods of class interruption. Moreover, we found that gradual and county closures may be slightly more easily applicable in practice as they are less sensitive to the value of the excess absenteeism threshold triggering the start of the intervention. These findings suggest that policy makers could consider school closure policies more diffusely as response strategy to influenza epidemics and pandemics, and the fact that some countries already have some experience of gradual or regional closures for seasonal influenza outbreaks demonstrates that logistic and feasibility challenges of school closure strategies can be to some extent overcome.

HIV status awareness, partnership dissolution and HIV transmission in generalized epidemics.

Directory of Open Access Journals (Sweden)

Georges Reniers

Full Text Available HIV status aware couples with at least one HIV positive partner are characterized by high separation and divorce rates. This phenomenon is often described as a corollary of couples HIV Testing and Counseling (HTC that ought to be minimized. In this contribution, we demonstrate the implications of partnership dissolution in serodiscordant couples for the propagation of HIV.We develop a compartmental model to study epidemic outcomes of elevated partnership dissolution rates in serodiscordant couples and parameterize it with estimates from population-based data (Rakai, Uganda.Via its effect on partnership dissolution, every percentage point increase in HIV status awareness reduces HIV incidence in monogamous populations by 0.27 percent for women and 0.63 percent for men. These effects are even larger when the assumption of monogamy can be relaxed, but are moderated by other behavior changes (e.g., increased condom use in HIV status aware serodiscordant partnerships. When these behavior changes are taken into account, each percentage point increase in HIV status awareness reduces HIV incidence by 0.13 and 0.32 percent for women and men, respectively (assuming monogamy. The partnership dissolution effect exists because it decreases the fraction of serodiscordant couples in the population and prolongs the time that individuals spend outside partnerships.Our model predicts that elevated partnership dissolution rates in HIV status aware serodiscordant couples reduce the spread of HIV. As a consequence, the full impact of couples HTC for HIV prevention is probably larger than recognized to date. Particularly high partnership dissolution rates in female positive serodiscordant couples contribute to the gender imbalance in HIV infections.

Dynamical Interplay between Awareness and Epidemic Spreading in Multiplex Networks

Science.gov (United States)

Granell, Clara; Gómez, Sergio; Arenas, Alex

2013-09-01

We present the analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the information awareness to prevent its infection, on top of multiplex networks. This scenario is representative of an epidemic process spreading on a network of persistent real contacts, and a cyclic information awareness process diffusing in the network of virtual social contacts between the same individuals. The topology corresponds to a multiplex network where two diffusive processes are interacting affecting each other. The analysis using a microscopic Markov chain approach reveals the phase diagram of the incidence of the epidemics and allows us to capture the evolution of the epidemic threshold depending on the topological structure of the multiplex and the interrelation with the awareness process. Interestingly, the critical point for the onset of the epidemics has a critical value (metacritical point) defined by the awareness dynamics and the topology of the virtual network, from which the onset increases and the epidemics incidence decreases.

Dynamical interplay between awareness and epidemic spreading in multiplex networks.

Science.gov (United States)

Granell, Clara; Gómez, Sergio; Arenas, Alex

2013-09-20

We present the analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the information awareness to prevent its infection, on top of multiplex networks. This scenario is representative of an epidemic process spreading on a network of persistent real contacts, and a cyclic information awareness process diffusing in the network of virtual social contacts between the same individuals. The topology corresponds to a multiplex network where two diffusive processes are interacting affecting each other. The analysis using a microscopic Markov chain approach reveals the phase diagram of the incidence of the epidemics and allows us to capture the evolution of the epidemic threshold depending on the topological structure of the multiplex and the interrelation with the awareness process. Interestingly, the critical point for the onset of the epidemics has a critical value (metacritical point) defined by the awareness dynamics and the topology of the virtual network, from which the onset increases and the epidemics incidence decreases.

FluTE, a publicly available stochastic influenza epidemic simulation model.

Directory of Open Access Journals (Sweden)

Dennis L Chao

2010-01-01

Full Text Available Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them. To help prepare for future influenza seasonal epidemics or pandemics, we developed a new stochastic model of the spread of influenza across a large population. Individuals in this model have realistic social contact networks, and transmission and infections are based on the current state of knowledge of the natural history of influenza. The model has been calibrated so that outcomes are consistent with the 1957/1958 Asian A(H2N2 and 2009 pandemic A(H1N1 influenza viruses. We present examples of how this model can be used to study the dynamics of influenza epidemics in the United States and simulate how to mitigate or delay them using pharmaceutical interventions and social distancing measures. Computer simulation models play an essential role in informing public policy and evaluating pandemic preparedness plans. We have made the source code of this model publicly available to encourage its use and further development.

FluTE, a publicly available stochastic influenza epidemic simulation model.

Science.gov (United States)

Chao, Dennis L; Halloran, M Elizabeth; Obenchain, Valerie J; Longini, Ira M

2010-01-29

Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them. To help prepare for future influenza seasonal epidemics or pandemics, we developed a new stochastic model of the spread of influenza across a large population. Individuals in this model have realistic social contact networks, and transmission and infections are based on the current state of knowledge of the natural history of influenza. The model has been calibrated so that outcomes are consistent with the 1957/1958 Asian A(H2N2) and 2009 pandemic A(H1N1) influenza viruses. We present examples of how this model can be used to study the dynamics of influenza epidemics in the United States and simulate how to mitigate or delay them using pharmaceutical interventions and social distancing measures. Computer simulation models play an essential role in informing public policy and evaluating pandemic preparedness plans. We have made the source code of this model publicly available to encourage its use and further development.

Epidemic spreading in networks with nonrandom long-range interactions

Science.gov (United States)

Estrada, Ernesto; Kalala-Mutombo, Franck; Valverde-Colmeiro, Alba

2011-09-01

An “infection,” understood here in a very broad sense, can be propagated through the network of social contacts among individuals. These social contacts include both “close” contacts and “casual” encounters among individuals in transport, leisure, shopping, etc. Knowing the first through the study of the social networks is not a difficult task, but having a clear picture of the network of casual contacts is a very hard problem in a society of increasing mobility. Here we assume, on the basis of several pieces of empirical evidence, that the casual contacts between two individuals are a function of their social distance in the network of close contacts. Then, we assume that we know the network of close contacts and infer the casual encounters by means of nonrandom long-range (LR) interactions determined by the social proximity of the two individuals. This approach is then implemented in a susceptible-infected-susceptible (SIS) model accounting for the spread of infections in complex networks. A parameter called “conductance” controls the feasibility of those casual encounters. In a zero conductance network only contagion through close contacts is allowed. As the conductance increases the probability of having casual encounters also increases. We show here that as the conductance parameter increases, the rate of propagation increases dramatically and the infection is less likely to die out. This increment is particularly marked in networks with scale-free degree distributions, where infections easily become epidemics. Our model provides a general framework for studying epidemic spreading in networks with arbitrary topology with and without casual contacts accounted for by means of LR interactions.

A stochastic modeling of recurrent measles epidemic | Kassem ...

African Journals Online (AJOL)

A simple stochastic mathematical model is developed and investigated for the dynamics of measles epidemic. The model, which is a multi-dimensional diffusion process, includes susceptible individuals, latent (exposed), infected and removed individuals. Stochastic effects are assumed to arise in the process of infection of ...

Epidemic spreading and immunization strategy in multiplex networks

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Alvarez Zuzek, Lucila G.; Buono, Camila; Braunstein, Lidia A.

2015-09-01

A more connected world has brought major consequences such as facilitate the spread of diseases all over the world to quickly become epidemics, reason why researchers are concentrated in modeling the propagation of epidemics and outbreaks in multilayer networks. In this networks all nodes interact in different layers with different type of links. However, in many scenarios such as in the society, a multiplex network framework is not completely suitable since not all individuals participate in all layers. In this paper, we use a partially overlapped, multiplex network where only a fraction of the individuals are shared by the layers. We develop a mitigation strategy for stopping a disease propagation, considering the Susceptible-Infected- Recover model, in a system consisted by two layers. We consider a random immunization in one of the layers and study the effect of the overlapping fraction in both, the propagation of the disease and the immunization strategy. Using branching theory, we study this scenario theoretically and via simulations and find a lower epidemic threshold than in the case without strategy.

A ‘post-honeymoon’ measles epidemic in Burundi: mathematical model-based analysis and implications for vaccination timing

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Katelyn C. Corey

2016-09-01

Full Text Available Using a mathematical model with realistic demography, we analyze a large outbreak of measles in Muyinga sector in rural Burundi in 1988–1989. We generate simulated epidemic curves and age × time epidemic surfaces, which we qualitatively and quantitatively compare with the data. Our findings suggest that supplementary immunization activities (SIAs should be used in places where routine vaccination cannot keep up with the increasing numbers of susceptible individuals resulting from population growth or from logistical problems such as cold chain maintenance. We use the model to characterize the relationship between SIA frequency and SIA age range necessary to suppress measles outbreaks. If SIAs are less frequent, they must expand their target age range.

Heterogeneous Epidemic Model for Assessing Data Dissemination in Opportunistic Networks

DEFF Research Database (Denmark)

Rozanova, Liudmila; Alekseev, Vadim; Temerev, Alexander

2014-01-01

that amount of data transferred between network nodes possesses a Pareto distribution, implying scale-free properties. In this context, more heterogeneity in susceptibility means the less severe epidemic progression, and, on the contrary, more heterogeneity in infectivity leads to more severe epidemics...... — assuming that the other parameter (either heterogeneity or susceptibility) stays fixed. The results are general enough to be useful for estimating the epidemic progression with no significant acquired immunity — in the cases where Pareto distribution holds....

Phylogenetics of the Danish HIV epidemic

DEFF Research Database (Denmark)

Audelin, Anne Margrethe; Cowan, Susan A; Obel, Niels

2013-01-01

BACKGROUND:: In Denmark 300 new individuals are diagnosed with HIV every year, despite decades of public health campaigns aimed to raise awareness of potential risk behaviour for HIV transmission. It is important to identify the driving forces of the epidemic, to enable more targeted campaigns...

Detection of Severe Respiratory Disease Epidemic Outbreaks by CUSUM-Based Overcrowd-Severe-Respiratory-Disease-Index Model

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Carlos Polanco

2013-01-01

Full Text Available A severe respiratory disease epidemic outbreak correlates with a high demand of specific supplies and specialized personnel to hold it back in a wide region or set of regions; these supplies would be beds, storage areas, hemodynamic monitors, and mechanical ventilators, as well as physicians, respiratory technicians, and specialized nurses. We describe an online cumulative sum based model named Overcrowd-Severe-Respiratory-Disease-Index based on the Modified Overcrowd Index that simultaneously monitors and informs the demand of those supplies and personnel in a healthcare network generating early warnings of severe respiratory disease epidemic outbreaks through the interpretation of such variables. A post hoc historical archive is generated, helping physicians in charge to improve the transit and future allocation of supplies in the entire hospital network during the outbreak. The model was thoroughly verified in a virtual scenario, generating multiple epidemic outbreaks in a 6-year span for a 13-hospital network. When it was superimposed over the H1N1 influenza outbreak census (2008–2010 taken by the National Institute of Medical Sciences and Nutrition Salvador Zubiran in Mexico City, it showed that it is an effective algorithm to notify early warnings of severe respiratory disease epidemic outbreaks with a minimal rate of false alerts.

Detection of Severe Respiratory Disease Epidemic Outbreaks by CUSUM-Based Overcrowd-Severe-Respiratory-Disease-Index Model

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Castañón-González, Jorge Alberto; Macías, Alejandro E.; Samaniego, José Lino; Buhse, Thomas; Villanueva-Martínez, Sebastián

2013-01-01

A severe respiratory disease epidemic outbreak correlates with a high demand of specific supplies and specialized personnel to hold it back in a wide region or set of regions; these supplies would be beds, storage areas, hemodynamic monitors, and mechanical ventilators, as well as physicians, respiratory technicians, and specialized nurses. We describe an online cumulative sum based model named Overcrowd-Severe-Respiratory-Disease-Index based on the Modified Overcrowd Index that simultaneously monitors and informs the demand of those supplies and personnel in a healthcare network generating early warnings of severe respiratory disease epidemic outbreaks through the interpretation of such variables. A post hoc historical archive is generated, helping physicians in charge to improve the transit and future allocation of supplies in the entire hospital network during the outbreak. The model was thoroughly verified in a virtual scenario, generating multiple epidemic outbreaks in a 6-year span for a 13-hospital network. When it was superimposed over the H1N1 influenza outbreak census (2008–2010) taken by the National Institute of Medical Sciences and Nutrition Salvador Zubiran in Mexico City, it showed that it is an effective algorithm to notify early warnings of severe respiratory disease epidemic outbreaks with a minimal rate of false alerts. PMID:24069063

Five challenges for stochastic epidemic models involving global transmission

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Tom Britton

2015-03-01

Full Text Available The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. Simple as they are, there are still several open problems for such models. For example, when will such an epidemic go extinct and with what probability (questions depending on the population being fixed, changing or growing? How can a model be defined explaining the sometimes observed scenario of frequent mid-sized epidemic outbreaks? How can evolution of the infectious agent transmission rates be modelled and fitted to data in a robust way?

Ebola hemorrhagic fever outbreaks: strategies for effective epidemic management, containment and control.

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Matua, Gerald Amandu; Van der Wal, Dirk Mostert; Locsin, Rozzano C

2015-01-01

Ebola hemorrhagic fever, caused by the highly virulent RNA virus of the filoviridae family, has become one of the world's most feared pathogens. The virus induces acute fever and death, often associated with hemorrhagic symptoms in up to 90% of infected patients. The known sub-types of the virus are Zaire, Sudan, Taï Forest, Bundibugyo and Reston Ebola viruses. In the past, outbreaks were limited to the East and Central African tropical belt with the exception of Ebola Reston outbreaks that occurred in animal facilities in the Philippines, USA and Italy. The on-going outbreak in West Africa that is causing numerous deaths and severe socio-economic challenges has resulted in widespread anxiety globally. This panic may be attributed to the intense media interest, the rapid spread of the virus to other countries like United States and Spain, and moreover, to the absence of an approved treatment or vaccine. Informed by this widespread fear and anxiety, we analyzed the commonly used strategies to manage and control Ebola outbreaks and proposed new approaches that could improve epidemic management and control during future outbreaks. We based our recommendations on epidemic management practices employed during recent outbreaks in East, Central and West Africa, and synthesis of peer-reviewed publications as well as published "field" information from individuals and organizations recently involved in the management of Ebola epidemics. The current epidemic management approaches are largely "reactive", with containment efforts aimed at halting spread of existing outbreaks. We recommend that for better outcomes, in addition to "reactive" interventions, "pre-emptive" strategies also need to be instituted. We conclude that emphasizing both "reactive" and "pre-emptive" strategies is more likely to lead to better epidemic preparedness and response at individual, community, institutional, and government levels, resulting in timely containment of future Ebola outbreaks. Copyright

Evaluating neighborhood structures for modeling intercity diffusion of large-scale dengue epidemics.

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Wen, Tzai-Hung; Hsu, Ching-Shun; Hu, Ming-Che

2018-05-03

Dengue fever is a vector-borne infectious disease that is transmitted by contact between vector mosquitoes and susceptible hosts. The literature has addressed the issue on quantifying the effect of individual mobility on dengue transmission. However, there are methodological concerns in the spatial regression model configuration for examining the effect of intercity-scale human mobility on dengue diffusion. The purposes of the study are to investigate the influence of neighborhood structures on intercity epidemic progression from pre-epidemic to epidemic periods and to compare definitions of different neighborhood structures for interpreting the spread of dengue epidemics. We proposed a framework for assessing the effect of model configurations on dengue incidence in 2014 and 2015, which were the most severe outbreaks in 70 years in Taiwan. Compared with the conventional model configuration in spatial regression analysis, our proposed model used a radiation model, which reflects population flow between townships, as a spatial weight to capture the structure of human mobility. The results of our model demonstrate better model fitting performance, indicating that the structure of human mobility has better explanatory power in dengue diffusion than the geometric structure of administration boundaries and geographic distance between centroids of cities. We also identified spatial-temporal hierarchy of dengue diffusion: dengue incidence would be influenced by its immediate neighboring townships during pre-epidemic and epidemic periods, and also with more distant neighbors (based on mobility) in pre-epidemic periods. Our findings suggest that the structure of population mobility could more reasonably capture urban-to-urban interactions, which implies that the hub cities could be a "bridge" for large-scale transmission and make townships that immediately connect to hub cities more vulnerable to dengue epidemics.

Sexual learning among East African adolescents in the context of generalized HIV epidemics: A systematic qualitative meta-synthesis.

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Amelia S Knopf

Full Text Available AIDS-related illness is the leading cause of mortality for adolescents in sub-Saharan Africa. Together, Kenya, Tanzania, and Uganda account for 21% of HIV-infected adolescents in sub-Saharan Africa. The United Nations framework for addressing the epidemic among adolescents calls for comprehensive sexual and reproductive health education. These HIV prevention efforts could be informed by a synthesis of existing research about the formal and informal sexual education of adolescents in countries experiencing generalized epidemics. The purpose of this study was to describe the process of sexual learning among East African adolescents living in the context of generalized HIV epidemics.Qualitative metasynthesis, a systematic procedure for integrating the results of multiple qualitative studies addressing a similar phenomenon, was used. Thirty-two research reports met study inclusion criteria. The reports were assessed in a four-step analytic process: appraisal, classification of findings, synthesis of findings, and construction of a framework depicting the process of sexual learning in this population.The framework includes three phases of sexual learning: 1 being primed for sex, 2 making sense of sex, and 3 having sexual experiences. Adolescents were primed for sex through gender norms, cultural practices, and economic structures as well as through conversations and formal instruction. They made sense of sex by acquiring information about sexual intercourse, reproduction and pregnancy, sexually transmitted infections, and relationships and by developing a variety of beliefs and attitudes about these topics. Some adolescents described having sexual experiences that met wants or needs, but many experienced sex that was coerced or violent. Whether sex was wanted, coerced, or violent, adolescents experienced worry about sexually transmitted infections or premarital pregnancy.The three phases of sexual learning interact to shape adolescents' sexual lives

Discrete stochastic analogs of Erlang epidemic models.

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Getz, Wayne M; Dougherty, Eric R

2018-12-01

Erlang differential equation models of epidemic processes provide more realistic disease-class transition dynamics from susceptible (S) to exposed (E) to infectious (I) and removed (R) categories than the ubiquitous SEIR model. The latter is itself is at one end of the spectrum of Erlang SE[Formula: see text]I[Formula: see text]R models with [Formula: see text] concatenated E compartments and [Formula: see text] concatenated I compartments. Discrete-time models, however, are computationally much simpler to simulate and fit to epidemic outbreak data than continuous-time differential equations, and are also much more readily extended to include demographic and other types of stochasticity. Here we formulate discrete-time deterministic analogs of the Erlang models, and their stochastic extension, based on a time-to-go distributional principle. Depending on which distributions are used (e.g. discretized Erlang, Gamma, Beta, or Uniform distributions), we demonstrate that our formulation represents both a discretization of Erlang epidemic models and generalizations thereof. We consider the challenges of fitting SE[Formula: see text]I[Formula: see text]R models and our discrete-time analog to data (the recent outbreak of Ebola in Liberia). We demonstrate that the latter performs much better than the former; although confining fits to strict SEIR formulations reduces the numerical challenges, but sacrifices best-fit likelihood scores by at least 7%.

[Hippocrates. Aphorisms and Epidemics III. Two clinical texts].

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Frøland, Anders

2015-01-01

The two Hippocratic texts, Aphorisms and Epidemics III, have not been translated into Danish previously. The Aphorisms are 412 short, pithy statements, mostly on the prognosis in relation to certain symptoms in the course of the diseases, very often febrile. The Aphorisms begin with the famous words: "Life is short, the Art long, opportunity fleeting, experiment treacherous, judgment difficult." (Transl. W H S Jones [22]). Epidemics III consists of 28 case histories, again mostly of febrile patients, but also of observations on the connection of the seasons with general morbidity and mortality. The author describes an epidemic, which in some respects resembles Thucydides' report on the plague in Athens in 430 BC. It is suggested, that observations as have been recorded in the seven Hippocratic texts on epidemic diseases are the material on which prognostic statements as those collected in the Aphorisms are founded.

Rainfall mediations in the spreading of epidemic cholera

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Righetto, L.; Bertuzzo, E.; Mari, L.; Schild, E.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

2013-10-01

Following the empirical evidence of a clear correlation between rainfall events and cholera resurgence that was observed in particular during the recent outbreak in Haiti, a spatially explicit model of epidemic cholera is re-examined. Specifically, we test a multivariate Poisson rainfall generator, with parameters varying in space and time, as a driver of enhanced disease transmission. The relevance of the issue relates to the key insight that predictive mathematical models may provide into the course of an ongoing cholera epidemic aiding emergency management (say, in allocating life-saving supplies or health care staff) or in evaluating alternative management strategies. Our model consists of a set of dynamical equations (SIRB-like i.e. subdivided into the compartments of Susceptible, Infected and Recovered individuals, and including a balance of Bacterial concentrations in the water reservoir) describing a connected network of human communities where the infection results from the exposure to excess concentrations of pathogens in the water. These, in turn, are driven by rainfall washout of open-air defecation sites or cesspool overflows, hydrologic transport through waterways and by mobility of susceptible and infected individuals. We perform an a posteriori analysis (from the beginning of the epidemic in October 2010 until December 2011) to test the model reliability in predicting cholera cases and in testing control measures, involving vaccination and sanitation campaigns, for the ongoing epidemic. Even though predicting reliably the timing of the epidemic resurgence proves difficult due to rainfall inter-annual variability, we find that the model can reasonably quantify the total number of reported infection cases in the selected time-span. We then run a multi-seasonal prediction of the course of the epidemic until December 2015, to investigate conditions for further resurgences and endemicity of cholera in the region with a view to policies which may bring to

Disadvantaged Social Groups and the Cigarette Epidemic: Limits of the Diffusion of Innovations Vision

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Myriam Khlat

2016-12-01

Full Text Available The original four-stage model of the cigarette epidemic has been extended with diffusion of innovations theory to reflect socio-economic differences in cigarette use. Recently, two revisions of the model have been proposed: (1 separate analysis of the epidemic stages for men and women, in order to improve generalization to developing countries, and; (2 addition of a fifth stage to the smoking epidemic, in order to account for the persistence of smoking in disadvantaged social groups. By developing a cohort perspective spanning a 35-year time period in France and the USA, we uncover distinctive features which challenge the currently held vision on the evolution of smoking inequalities within the framework of the cigarette epidemic. We argue that the reason for which the model may not be fit to the lower educated is that the imitation mechanism underlying the diffusion of innovations works well with regard to adoption of the habit, but is much less relevant with regard to its rejection. Based on those observations, we support the idea that the nature and timing of the epidemic differs enough to treat the stages separately for high and low education groups, and discuss policy implications.

Effects of epidemic threshold definition on disease spread statistics

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Lagorio, C.; Migueles, M. V.; Braunstein, L. A.; López, E.; Macri, P. A.

2009-03-01

We study the statistical properties of SIR epidemics in random networks, when an epidemic is defined as only those SIR propagations that reach or exceed a minimum size sc. Using percolation theory to calculate the average fractional size of an epidemic, we find that the strength of the spanning link percolation cluster P∞ is an upper bound to . For small values of sc, P∞ is no longer a good approximation, and the average fractional size has to be computed directly. We find that the choice of sc is generally (but not always) guided by the network structure and the value of T of the disease in question. If the goal is to always obtain P∞ as the average epidemic size, one should choose sc to be the typical size of the largest percolation cluster at the critical percolation threshold for the transmissibility. We also study Q, the probability that an SIR propagation reaches the epidemic mass sc, and find that it is well characterized by percolation theory. We apply our results to real networks (DIMES and Tracerouter) to measure the consequences of the choice sc on predictions of average outcome sizes of computer failure epidemics.

[Observations on the 1348 plague epidemic. Measures taken to combat its tragic effects and avoid epidemic recrudescence].

Science.gov (United States)

Sabbatani, Sergio

2003-03-01

Italian and German city-states, the emerging nations (France, England, Austria, Spain, Holland) developed and adopted procedures to control the epidemic - at the first on an ad hoc basis, then permanently. Sometimes success was achieved but always at a high price on the part of the individual and the local community. The path to an epidemic-free existence for humankind was still a long one.

Risk-based input-output analysis of influenza epidemic consequences on interdependent workforce sectors.

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Santos, Joost R; May, Larissa; Haimar, Amine El

2013-09-01

Outbreaks of contagious diseases underscore the ever-looming threat of new epidemics. Compared to other disasters that inflict physical damage to infrastructure systems, epidemics can have more devastating and prolonged impacts on the population. This article investigates the interdependent economic and productivity risks resulting from epidemic-induced workforce absenteeism. In particular, we develop a dynamic input-output model capable of generating sector-disaggregated economic losses based on different magnitudes of workforce disruptions. An ex post analysis of the 2009 H1N1 pandemic in the national capital region (NCR) reveals the distribution of consequences across different economic sectors. Consequences are categorized into two metrics: (i) economic loss, which measures the magnitude of monetary losses incurred in each sector, and (ii) inoperability, which measures the normalized monetary losses incurred in each sector relative to the total economic output of that sector. For a simulated mild pandemic scenario in NCR, two distinct rankings are generated using the economic loss and inoperability metrics. Results indicate that the majority of the critical sectors ranked according to the economic loss metric comprise of sectors that contribute the most to the NCR's gross domestic product (e.g., federal government enterprises). In contrast, the majority of the critical sectors generated by the inoperability metric include sectors that are involved with epidemic management (e.g., hospitals). Hence, prioritizing sectors for recovery necessitates consideration of the balance between economic loss, inoperability, and other objectives. Although applied specifically to the NCR, the proposed methodology can be customized for other regions. © 2012 Society for Risk Analysis.

Suppressing epidemic spreading by risk-averse migration in dynamical networks

Science.gov (United States)

Yang, Han-Xin; Tang, Ming; Wang, Zhen

2018-01-01

In this paper, we study the interplay between individual behaviors and epidemic spreading in a dynamical network. We distribute agents on a square-shaped region with periodic boundary conditions. Every agent is regarded as a node of the network and a wireless link is established between two agents if their geographical distance is less than a certain radius. At each time, every agent assesses the epidemic situation and make decisions on whether it should stay in or leave its current place. An agent will leave its current place with a speed if the number of infected neighbors reaches or exceeds a critical value E. Owing to the movement of agents, the network's structure is dynamical. Interestingly, we find that there exists an optimal value of E leading to the maximum epidemic threshold. This means that epidemic spreading can be effectively controlled by risk-averse migration. Besides, we find that the epidemic threshold increases as the recovering rate increases, decreases as the contact radius increases, and is maximized by an optimal moving speed. Our findings offer a deeper understanding of epidemic spreading in dynamical networks.

Discrete time Markov chains (DTMC) susceptible infected susceptible (SIS) epidemic model with two pathogens in two patches

Science.gov (United States)

Lismawati, Eka; Respatiwulan; Widyaningsih, Purnami

2017-06-01

The SIS epidemic model describes the pattern of disease spread with characteristics that recovered individuals can be infected more than once. The number of susceptible and infected individuals every time follows the discrete time Markov process. It can be represented by the discrete time Markov chains (DTMC) SIS. The DTMC SIS epidemic model can be developed for two pathogens in two patches. The aims of this paper are to reconstruct and to apply the DTMC SIS epidemic model with two pathogens in two patches. The model was presented as transition probabilities. The application of the model obtain that the number of susceptible individuals decreases while the number of infected individuals increases for each pathogen in each patch.

Phenotypes of individuals affected by airborne chemicals in the general population

DEFF Research Database (Denmark)

Berg, Nikolaj Drimer; Linneberg, A.; Dirksen, Asger

2009-01-01

to symptoms than less severely affected individuals, and the number of symptoms was more predictive for severity than the number of exposures. Most predictive for the severity of reported symptoms were CNS-symptoms other than headache (OR = 3.2, P ... (OR = 2.0, P = 0.001). CONCLUSION: CNS-symptoms except from headache were a main characteristic of individuals severely affected by common chemical exposures in a general population-based sample...

Estimating incidence from prevalence in generalised HIV epidemics: methods and validation.

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Timothy B Hallett

2008-04-01

Full Text Available HIV surveillance of generalised epidemics in Africa primarily relies on prevalence at antenatal clinics, but estimates of incidence in the general population would be more useful. Repeated cross-sectional measures of HIV prevalence are now becoming available for general populations in many countries, and we aim to develop and validate methods that use these data to estimate HIV incidence.Two methods were developed that decompose observed changes in prevalence between two serosurveys into the contributions of new infections and mortality. Method 1 uses cohort mortality rates, and method 2 uses information on survival after infection. The performance of these two methods was assessed using simulated data from a mathematical model and actual data from three community-based cohort studies in Africa. Comparison with simulated data indicated that these methods can accurately estimates incidence rates and changes in incidence in a variety of epidemic conditions. Method 1 is simple to implement but relies on locally appropriate mortality data, whilst method 2 can make use of the same survival distribution in a wide range of scenarios. The estimates from both methods are within the 95% confidence intervals of almost all actual measurements of HIV incidence in adults and young people, and the patterns of incidence over age are correctly captured.It is possible to estimate incidence from cross-sectional prevalence data with sufficient accuracy to monitor the HIV epidemic. Although these methods will theoretically work in any context, we have able to test them only in southern and eastern Africa, where HIV epidemics are mature and generalised. The choice of method will depend on the local availability of HIV mortality data.

Evaluation and comparison of predictive individual-level general surrogates.

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Gabriel, Erin E; Sachs, Michael C; Halloran, M Elizabeth

2018-07-01

An intermediate response measure that accurately predicts efficacy in a new setting at the individual level could be used both for prediction and personalized medical decisions. In this article, we define a predictive individual-level general surrogate (PIGS), which is an individual-level intermediate response that can be used to accurately predict individual efficacy in a new setting. While methods for evaluating trial-level general surrogates, which are predictors of trial-level efficacy, have been developed previously, few, if any, methods have been developed to evaluate individual-level general surrogates, and no methods have formalized the use of cross-validation to quantify the expected prediction error. Our proposed method uses existing methods of individual-level surrogate evaluation within a given clinical trial setting in combination with cross-validation over a set of clinical trials to evaluate surrogate quality and to estimate the absolute prediction error that is expected in a new trial setting when using a PIGS. Simulations show that our method performs well across a variety of scenarios. We use our method to evaluate and to compare candidate individual-level general surrogates over a set of multi-national trials of a pentavalent rotavirus vaccine.

Degree of host susceptibility in the initial disease outbreak influences subsequent epidemic spread

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Severns, Paul M.; Estep, Laura K.; Sackett, Kathryn E.; Mundt, Christopher C.

2014-01-01

Summary Disease epidemics typically begin as an outbreak of a relatively small, spatially explicit population of infected individuals (focus), in which disease prevalence increases and rapidly spreads into the uninfected, at-risk population. Studies of epidemic spread typically address factors influencing disease spread through the at-risk population, but the initial outbreak may strongly influence spread of the subsequent epidemic.We initiated wheat stripe rust Puccinia striiformis f. sp. tritici epidemics to assess the influence of the focus on final disease prevalence when the degree of disease susceptibility differed between the at-risk and focus populations.When the focus/at-risk plantings consisted of partially genetic resistant and susceptible cultivars, final disease prevalence was statistically indistinguishable from epidemics produced by the focus cultivar in monoculture. In these experimental epidemics, disease prevalence was not influenced by the transition into an at-risk population that differed in disease susceptibility. Instead, the focus appeared to exert a dominant influence on the subsequent epidemic.Final disease prevalence was not consistently attributable to either the focus or the at-risk population when focus/at-risk populations were planted in a factorial set-up with a mixture (~28% susceptible and 72% resistant) and susceptible individuals. In these experimental epidemics, spatial heterogeneity in disease susceptibility within the at-risk population appeared to counter the dominant influence of the focus.Cessation of spore production from the focus (through fungicide/glyphosate application) after 1.3 generations of stripe rust spread did not reduce final disease prevalence, indicating that the focus influence on disease spread is established early in the epidemic.Synthesis and applications. Our experiments indicated that outbreak conditions can be highly influential on epidemic spread, even when disease resistance in the at-risk population

Optimal Control of Interdependent Epidemics in Complex Networks

OpenAIRE

Chen, Juntao; Zhang, Rui; Zhu, Quanyan

2017-01-01

Optimal control of interdependent epidemics spreading over complex networks is a critical issue. We first establish a framework to capture the coupling between two epidemics, and then analyze the system's equilibrium states by categorizing them into three classes, and deriving their stability conditions. The designed control strategy globally optimizes the trade-off between the control cost and the severity of epidemics in the network. A gradient descent algorithm based on a fixed point itera...

Epidemic spreading on contact networks with adaptive weights.

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Zhu, Guanghu; Chen, Guanrong; Xu, Xin-Jian; Fu, Xinchu

2013-01-21

The heterogeneous patterns of interactions within a population are often described by contact networks, but the variety and adaptivity of contact strengths are usually ignored. This paper proposes a modified epidemic SIS model with a birth-death process and nonlinear infectivity on an adaptive and weighted contact network. The links' weights, named as 'adaptive weights', which indicate the intimacy or familiarity between two connected individuals, will reduce as the disease develops. Through mathematical and numerical analyses, conditions are established for population extermination, disease extinction and infection persistence. Particularly, it is found that the fixed weights setting can trigger the epidemic incidence, and that the adaptivity of weights cannot change the epidemic threshold but it can accelerate the disease decay and lower the endemic level. Finally, some corresponding control measures are suggested. Copyright © 2012 Elsevier Ltd. All rights reserved.

Impact of information on intentions to vaccinate in a potential epidemic: Swine-origin Influenza A (H1N1).

Science.gov (United States)

Chanel, Olivier; Luchini, Stéphane; Massoni, Sébastien; Vergnaud, Jean-Christophe

2011-01-01

Vaccination campaigns to prevent the spread of epidemics are successful only if the targeted populations subscribe to the recommendations of health authorities. However, because compulsory vaccination is hardly conceivable in modern democracies, governments need to convince their populations through efficient and persuasive information campaigns. In the context of the swine-origin A (H1N1) 2009 pandemic, we use an interactive study among the general public in the South of France, with 175 participants, to explore what type of information can induce change in vaccination intentions at both aggregate and individual levels. We find that individual attitudes to vaccination are based on rational appraisal of the situation, and that it is information of a purely scientific nature that has the only significant positive effect on intention to vaccinate. Copyright © 2010 Elsevier Ltd. All rights reserved.

Dynamical interplay between awareness and epidemic spreading in multiplex networks

OpenAIRE

Granell, Clara; Gomez, Sergio; Arenas, Alex

2013-01-01

We present the analysis of the interrelation between two processes accounting for the spreading of an epidemics, and the information awareness to prevent its infection, on top of multiplex networks. This scenario is representative of an epidemic process spreading on a network of persistent real contacts, and a cyclic information awareness process diffusing in the network of virtual social contacts between the same individuals. The topology corresponds to a multiplex network where two diffusiv...

Epidemic spreading induced by diversity of agents' mobility.

Science.gov (United States)

Zhou, Jie; Chung, Ning Ning; Chew, Lock Yue; Lai, Choy Heng

2012-08-01

In this paper, we study the impact of the preference of an individual for public transport on the spread of infectious disease, through a quantity known as the public mobility. Our theoretical and numerical results based on a constructed model reveal that if the average public mobility of the agents is fixed, an increase in the diversity of the agents' public mobility reduces the epidemic threshold, beyond which an enhancement in the rate of infection is observed. Our findings provide an approach to improve the resistance of a society against infectious disease, while preserving the utilization rate of the public transportation system.

Behavioral Responses to Epidemics in an Online Experiment: Using Virtual Diseases to Study Human Behavior

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Chen, Frederick; Griffith, Amanda; Cottrell, Allin; Wong, Yue-Ling

2013-01-01

We report the results of a study we conducted using a simple multiplayer online game that simulates the spread of an infectious disease through a population composed of the players. We use our virtual epidemics game to examine how people respond to epidemics. The analysis shows that people's behavior is responsive to the cost of self-protection, the reported prevalence of disease, and their experiences earlier in the epidemic. Specifically, decreasing the cost of self-protection increases the rate of safe behavior. Higher reported prevalence also raises the likelihood that individuals would engage in self-protection, where the magnitude of this effect depends on how much time has elapsed in the epidemic. Individuals' experiences in terms of how often an infection was acquired when they did not engage in self-protection are another factor that determines whether they will invest in preventive measures later on. All else being equal, individuals who were infected at a higher rate are more likely to engage in self-protective behavior compared to those with a lower rate of infection. Lastly, fixing everything else, people's willingness to engage in safe behavior waxes or wanes over time, depending on the severity of an epidemic: when prevalence is high, people are more likely to adopt self-protective measures as time goes by; when prevalence is low, a ‘self-protection fatigue’ effect sets in whereby individuals are less willing to engage in safe behavior over time. PMID:23326360

Effective distances for epidemics spreading on complex networks

Science.gov (United States)

Iannelli, Flavio; Koher, Andreas; Brockmann, Dirk; Hövel, Philipp; Sokolov, Igor M.

2017-01-01

We show that the recently introduced logarithmic metrics used to predict disease arrival times on complex networks are approximations of more general network-based measures derived from random walks theory. Using the daily air-traffic transportation data we perform numerical experiments to compare the infection arrival time with this alternative metric that is obtained by accounting for multiple walks instead of only the most probable path. The comparison with direct simulations reveals a higher correlation compared to the shortest-path approach used previously. In addition our method allows to connect fundamental observables in epidemic spreading with the cumulant-generating function of the hitting time for a Markov chain. Our results provides a general and computationally efficient approach using only algebraic methods.

Alternative risk financing instruments for swine epidemics

NARCIS (Netherlands)

Meuwissen, M.P.M.; Asseldonk, van M.A.P.M.; Huirne, R.B.M.

2003-01-01

Swine epidemics can have very large devastating financial consequences. Governments generally bear the direct losses, such as the value of destroyed animals. Consequential losses, such as the losses resulting from empty buildings and movement standstills, are completely borne by the farmers (and

Dynamics of epidemic spreading with vaccination: Impact of social pressure and engagement

Science.gov (United States)

Pires, Marcelo A.; Crokidakis, Nuno

2017-02-01

In this work we consider a model of epidemic spreading coupled with an opinion dynamics in a fully-connected population. Regarding the opinion dynamics, the individuals may be in two distinct states, namely in favor or against a vaccination campaign. Individuals against the vaccination follow a standard SIS model, whereas the pro-vaccine individuals can also be in a third compartment, namely Vaccinated. In addition, the opinions change according to the majority-rule dynamics in groups with three individuals. We also consider that the vaccine can give permanent or temporary immunization to the individuals. By means of analytical calculations and computer simulations, we show that the opinion dynamics can drastically affect the disease propagation, and that the engagement of the pro-vaccine individuals can be crucial for stopping the epidemic spreading. The full numerical code for simulating the model is available from the authors' webpage.

A chaotic model for the epidemic of Ebola virus disease in West Africa (2013-2016)

Science.gov (United States)

Mangiarotti, Sylvain; Peyre, Marisa; Huc, Mireille

2016-11-01

An epidemic of Ebola Virus Disease (EVD) broke out in Guinea in December 2013. It was only identified in March 2014 while it had already spread out in Liberia and Sierra Leone. The spill over of the disease became uncontrollable and the epidemic could not be stopped before 2016. The time evolution of this epidemic is revisited here with the global modeling technique which was designed to obtain the deterministic models from single time series. A generalized formulation of this technique for multivariate time series is introduced. It is applied to the epidemic of EVD in West Africa focusing on the period between March 2014 and January 2015, that is, before any detected signs of weakening. Data gathered by the World Health Organization, based on the official publications of the Ministries of Health of the three main countries involved in this epidemic, are considered in our analysis. Two observed time series are used: the daily numbers of infections and deaths. A four-dimensional model producing a very complex dynamical behavior is obtained. The model is tested in order to investigate its skills and drawbacks. Our global analysis clearly helps to distinguish three main stages during the epidemic. A characterization of the obtained attractor is also performed. In particular, the topology of the chaotic attractor is analyzed and a skeleton is obtained for its structure.

Household demographic determinants of Ebola epidemic risk.

Science.gov (United States)

Adams, Ben

2016-03-07

A salient characteristic of Ebola, and some other infectious diseases such as Tuberculosis, is intense transmission among small groups of cohabitants and relatively limited indiscriminate transmission in the wider population. Here we consider a mathematical model for an Ebola epidemic in a population structured into households of equal size. We show that household size, a fundamental demographic unit, is a critical factor that determines the vulnerability of a community to epidemics, and the effort required to control them. Our analysis is based on the household reproduction number, but we also consider the basic reproduction number, intrinsic growth rate and final epidemic size. We show that, when other epidemiological parameters are kept the same, all of these quantifications of epidemic growth and size are increased by larger households and more intense within-household transmission. We go on to model epidemic control by case detection and isolation followed by household quarantine. We show that, if household quarantine is ineffective, the critical probability with which cases must be detected to halt an epidemic increases significantly with each increment in household size and may be a very challenging target for communities composed of large households. Effective quarantine may, however, mitigate the detrimental impact of large household sizes. We conclude that communities composed of large households are fundamentally more vulnerable to epidemics of infectious diseases primarily transmitted by close contact, and any assessment of control strategies for these epidemics should take into account the demographic structure of the population. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spread of epidemic disease on networks

Science.gov (United States)

Newman, M. E.

2002-07-01

The study of social networks, and in particular the spread of disease on networks, has attracted considerable recent attention in the physics community. In this paper, we show that a large class of standard epidemiological models, the so-called susceptible/infective/removed (SIR) models can be solved exactly on a wide variety of networks. In addition to the standard but unrealistic case of fixed infectiveness time and fixed and uncorrelated probability of transmission between all pairs of individuals, we solve cases in which times and probabilities are nonuniform and correlated. We also consider one simple case of an epidemic in a structured population, that of a sexually transmitted disease in a population divided into men and women. We confirm the correctness of our exact solutions with numerical simulations of SIR epidemics on networks.

Effect of risk perception on epidemic spreading in temporal networks

Science.gov (United States)

Moinet, Antoine; Pastor-Satorras, Romualdo; Barrat, Alain

2018-01-01

Many progresses in the understanding of epidemic spreading models have been obtained thanks to numerous modeling efforts and analytical and numerical studies, considering host populations with very different structures and properties, including complex and temporal interaction networks. Moreover, a number of recent studies have started to go beyond the assumption of an absence of coupling between the spread of a disease and the structure of the contacts on which it unfolds. Models including awareness of the spread have been proposed, to mimic possible precautionary measures taken by individuals that decrease their risk of infection, but have mostly considered static networks. Here, we adapt such a framework to the more realistic case of temporal networks of interactions between individuals. We study the resulting model by analytical and numerical means on both simple models of temporal networks and empirical time-resolved contact data. Analytical results show that the epidemic threshold is not affected by the awareness but that the prevalence can be significantly decreased. Numerical studies on synthetic temporal networks highlight, however, the presence of very strong finite-size effects, resulting in a significant shift of the effective epidemic threshold in the presence of risk awareness. For empirical contact networks, the awareness mechanism leads as well to a shift in the effective threshold and to a strong reduction of the epidemic prevalence.

Two approaches to forecast Ebola synthetic epidemics.

Science.gov (United States)

Champredon, David; Li, Michael; Bolker, Benjamin M; Dushoff, Jonathan

2018-03-01

We use two modelling approaches to forecast synthetic Ebola epidemics in the context of the RAPIDD Ebola Forecasting Challenge. The first approach is a standard stochastic compartmental model that aims to forecast incidence, hospitalization and deaths among both the general population and health care workers. The second is a model based on the renewal equation with latent variables that forecasts incidence in the whole population only. We describe fitting and forecasting procedures for each model and discuss their advantages and drawbacks. We did not find that one model was consistently better in forecasting than the other. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Epidemic extinction paths in complex networks

Science.gov (United States)

Hindes, Jason; Schwartz, Ira B.

2017-05-01

We study the extinction of long-lived epidemics on finite complex networks induced by intrinsic noise. Applying analytical techniques to the stochastic susceptible-infected-susceptible model, we predict the distribution of large fluctuations, the most probable or optimal path through a network that leads to a disease-free state from an endemic state, and the average extinction time in general configurations. Our predictions agree with Monte Carlo simulations on several networks, including synthetic weighted and degree-distributed networks with degree correlations, and an empirical high school contact network. In addition, our approach quantifies characteristic scaling patterns for the optimal path and distribution of large fluctuations, both near and away from the epidemic threshold, in networks with heterogeneous eigenvector centrality and degree distributions.

Eight challenges for network epidemic models

Directory of Open Access Journals (Sweden)

Lorenzo Pellis

2015-03-01

Full Text Available Networks offer a fertile framework for studying the spread of infection in human and animal populations. However, owing to the inherent high-dimensionality of networks themselves, modelling transmission through networks is mathematically and computationally challenging. Even the simplest network epidemic models present unanswered questions. Attempts to improve the practical usefulness of network models by including realistic features of contact networks and of host–pathogen biology (e.g. waning immunity have made some progress, but robust analytical results remain scarce. A more general theory is needed to understand the impact of network structure on the dynamics and control of infection. Here we identify a set of challenges that provide scope for active research in the field of network epidemic models.

The wisdom of crowds in action: Forecasting epidemic diseases with a web-based prediction market system.

Science.gov (United States)

Li, Eldon Y; Tung, Chen-Yuan; Chang, Shu-Hsun

2016-08-01

The quest for an effective system capable of monitoring and predicting the trends of epidemic diseases is a critical issue for communities worldwide. With the prevalence of Internet access, more and more researchers today are using data from both search engines and social media to improve the prediction accuracy. In particular, a prediction market system (PMS) exploits the wisdom of crowds on the Internet to effectively accomplish relatively high accuracy. This study presents the architecture of a PMS and demonstrates the matching mechanism of logarithmic market scoring rules. The system was implemented to predict infectious diseases in Taiwan with the wisdom of crowds in order to improve the accuracy of epidemic forecasting. The PMS architecture contains three design components: database clusters, market engine, and Web applications. The system accumulated knowledge from 126 health professionals for 31 weeks to predict five disease indicators: the confirmed cases of dengue fever, the confirmed cases of severe and complicated influenza, the rate of enterovirus infections, the rate of influenza-like illnesses, and the confirmed cases of severe and complicated enterovirus infection. Based on the winning ratio, the PMS predicts the trends of three out of five disease indicators more accurately than does the existing system that uses the five-year average values of historical data for the same weeks. In addition, the PMS with the matching mechanism of logarithmic market scoring rules is easy to understand for health professionals and applicable to predict all the five disease indicators. The PMS architecture of this study affords organizations and individuals to implement it for various purposes in our society. The system can continuously update the data and improve prediction accuracy in monitoring and forecasting the trends of epidemic diseases. Future researchers could replicate and apply the PMS demonstrated in this study to more infectious diseases and wider

Bilingual language control and general purpose cognitive control among individuals with bilingual aphasia: evidence based on negative priming and flanker tasks.

Science.gov (United States)

Dash, Tanya; Kar, Bhoomika R

2014-01-01

Bilingualism results in an added advantage with respect to cognitive control. The interaction between bilingual language control and general purpose cognitive control systems can also be understood by studying executive control among individuals with bilingual aphasia. objectives: The current study examined the subcomponents of cognitive control in bilingual aphasia. A case study approach was used to investigate whether cognitive control and language control are two separate systems and how factors related to bilingualism interact with control processes. Four individuals with bilingual aphasia performed a language background questionnaire, picture description task, and two experimental tasks (nonlinguistic negative priming task and linguistic and nonlinguistic versions of flanker task). A descriptive approach was used to analyse the data using reaction time and accuracy measures. The cumulative distribution function plots were used to visualize the variations in performance across conditions. The results highlight the distinction between general purpose cognitive control and bilingual language control mechanisms. All participants showed predominant use of the reactive control mechanism to compensate for the limited resources system. Independent yet interactive systems for bilingual language control and general purpose cognitive control were postulated based on the experimental data derived from individuals with bilingual aphasia.

Dynamics of epidemics outbreaks in heterogeneous populations

Science.gov (United States)

Brockmann, Dirk; Morales-Gallardo, Alejandro; Geisel, Theo

2007-03-01

The dynamics of epidemic outbreaks have been investigated in recent years within two alternative theoretical paradigms. The key parameter of mean field type of models such as the SIR model is the basic reproduction number R0, the average number of secondary infections caused by one infected individual. Recently, scale free network models have received much attention as they account for the high variability in the number of social contacts involved. These models predict an infinite basic reproduction number in some cases. We investigate the impact of heterogeneities of contact rates in a generic model for epidemic outbreaks. We present a system in which both the time periods of being infectious and the time periods between transmissions are Poissonian processes. The heterogeneities are introduced by means of strongly variable contact rates. In contrast to scale free network models we observe a finite basic reproduction number and, counterintuitively a smaller overall epidemic outbreak as compared to the homogeneous system. Our study thus reveals that heterogeneities in contact rates do not necessarily facilitate the spread to infectious disease but may well attenuate it.

Kin groups and trait groups: population structure and epidemic disease selection.

Science.gov (United States)

Fix, A G

1984-10-01

A Monte Carlo simulation based on the population structure of a small-scale human population, the Semai Senoi of Malaysia, has been developed to study the combined effects of group, kin, and individual selection. The population structure resembles D.S. Wilson's structured deme model in that local breeding populations (Semai settlements) are subdivided into trait groups (hamlets) that may be kin-structured and are not themselves demes. Additionally, settlement breeding populations are connected by two-dimensional stepping-stone migration approaching 30% per generation. Group and kin-structured group selection occur among hamlets the survivors of which then disperse to breed within the settlement population. Genetic drift is modeled by the process of hamlet formation; individual selection as a deterministic process, and stepping-stone migration as either random or kin-structured migrant groups. The mechanism for group selection is epidemics of infectious disease that can wipe out small hamlets particularly if most adults become sick and social life collapses. Genetic resistance to a disease is an individual attribute; however, hamlet groups with several resistant adults are less likely to disintegrate and experience high social mortality. A specific human gene, hemoglobin E, which confers resistance to malaria, is studied as an example of the process. The results of the simulations show that high genetic variance among hamlet groups may be generated by moderate degrees of kin-structuring. This strong microdifferentiation provides the potential for group selection. The effect of group selection in this case is rapid increase in gene frequencies among the total set of populations. In fact, group selection in concert with individual selection produced a faster rate of gene frequency increase among a set of 25 populations than the rate within a single unstructured population subject to deterministic individual selection. Such rapid evolution with plausible rates of

Epidemic typhus.

Science.gov (United States)

Bechah, Yassina; Capo, Christian; Mege, Jean-Louis; Raoult, Didier

2008-07-01

Epidemic typhus is transmitted to human beings by the body louse Pediculus humanus corporis. The disease is still considered a major threat by public-health authorities, despite the efficacy of antibiotics, because poor sanitary conditions are conducive to louse proliferation. Until recently, Rickettsia prowazekii, the causal agent, was thought to be confined to human beings and their body lice. Since 1975, R prowazekii infection in human beings has been related to contact with the flying squirrel Glaucomys volans in the USA. Moreover, Brill-Zinsser disease, a relapsed form of epidemic typhus that appears as sporadic cases many years after the initial infection, is unrelated to louse infestation. Stress or a waning immune system are likely to reactivate this earlier persistent infection, which could be the source of new epidemics when conditions facilitate louse infestation. Finally, R prowazekii is a potential category B bioterrorism agent, because it is stable in dried louse faeces and can be transmitted through aerosols. An increased understanding of the pathogenesis of epidemic typhus may be useful for protection against this bacterial threat.

Modeling Epidemics Spreading on Social Contact Networks.

Science.gov (United States)

Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

2015-09-01

Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.

Dengue epidemics and adverse obstetrical outcomes in French Guiana: a semi-ecological study

Science.gov (United States)

Hanf, Matthieu; Friedman, Eleanor; Basurko, Celia; Roger, Amaury; Bruncher, Pascal; Dussart, Philippe; Flamand, Claude; Carles, Gabriel; Buekens, Pierre; Breart, Gerard; Carme, Bernard; Nacher, Mathieu

2014-01-01

There are few studies on the obstetrical consequences of dengue fever during pregnancy. To determine whether dengue epidemics were associated with an increase in adverse obstetrical outcomes, a semi-ecological study combining individual data on obstetrical events from the perinatal registry and aggregated exposure data from the epidemiologic surveillance of dengue was conducted in Cayenne French Guiana between 2004 and 2007. After adjustment for individual risk factors, this semi-ecological analysis showed that an epidemic level of dengue transmission during the first trimester was associated with an increased risk of postpartum hemorrhage and preterm birth. The associated risks seemed to depend on the epidemic level. Despite its limitations, the present study suggests that dengue in the first trimester may be related to preterm birth and to postpartum bleeding, thus leading to specific hypotheses that should be tested in prospective studies. PMID:24341915

Environmental Factors Influencing Epidemic Cholera

Science.gov (United States)

Jutla, Antarpreet; Whitcombe, Elizabeth; Hasan, Nur; Haley, Bradd; Akanda, Ali; Huq, Anwar; Alam, Munir; Sack, R. Bradley; Colwell, Rita

2013-01-01

Cholera outbreak following the earthquake of 2010 in Haiti has reaffirmed that the disease is a major public health threat. Vibrio cholerae is autochthonous to aquatic environment, hence, it cannot be eradicated but hydroclimatology-based prediction and prevention is an achievable goal. Using data from the 1800s, we describe uniqueness in seasonality and mechanism of occurrence of cholera in the epidemic regions of Asia and Latin America. Epidemic regions are located near regional rivers and are characterized by sporadic outbreaks, which are likely to be initiated during episodes of prevailing warm air temperature with low river flows, creating favorable environmental conditions for growth of cholera bacteria. Heavy rainfall, through inundation or breakdown of sanitary infrastructure, accelerates interaction between contaminated water and human activities, resulting in an epidemic. This causal mechanism is markedly different from endemic cholera where tidal intrusion of seawater carrying bacteria from estuary to inland regions, results in outbreaks. PMID:23897993

Mean field theory of epidemic spreading with effective contacts on networks

International Nuclear Information System (INIS)

Wu, Qingchu; Chen, Shufang

2015-01-01

We present a general approach to the analysis of the susceptible-infected-susceptible model with effective contacts on networks, where each susceptible node will be infected with a certain probability only for effective contacts. In the network, each node has a given effective contact number. By using the one-vertex heterogenous mean-field (HMF) approximation and the pair HMF approximation, we obtain conditions for epidemic outbreak on degree-uncorrelated networks. Our results suggest that the epidemic threshold is closely related to the effective contact and its distribution. However, when the effective contact is only dependent of node degree, the epidemic threshold can be established by the degree distribution of networks.

Epidemics and dimensionality in hierarchical networks

Science.gov (United States)

Zheng, Da-Fang; Hui, P. M.; Trimper, Steffen; Zheng, Bo

2005-07-01

Epidemiological processes are studied within a recently proposed hierarchical network model using the susceptible-infected-refractory dynamics of an epidemic. Within the network model, a population may be characterized by H independent hierarchies or dimensions, each of which consists of groupings of individuals into layers of subgroups. Detailed numerical simulations reveal that for H>1, global spreading results regardless of the degree of homophily of the individuals forming a social circle. For H=1, a transition from global to local spread occurs as the population becomes decomposed into increasingly homophilous groups. Multiple dimensions in classifying individuals (nodes) thus make a society (computer network) highly susceptible to large-scale outbreaks of infectious diseases (viruses).

The effects of global awareness on the spreading of epidemics in multiplex networks

Science.gov (United States)

Zang, Haijuan

2018-02-01

It is increasingly recognized that understanding the complex interplay patterns between epidemic spreading and human behavioral is a key component of successful infection control efforts. In particular, individuals can obtain the information about epidemics and respond by altering their behaviors, which can affect the spreading dynamics as well. Besides, because the existence of herd-like behaviors, individuals are very easy to be influenced by the global awareness information. Here, in this paper, we propose a global awareness controlled spreading model (GACS) to explore the interplay between the coupled dynamical processes. Using the global microscopic Markov chain approach, we obtain the analytical results for the epidemic thresholds, which shows a high accuracy by comparison with lots of Monte Carlo simulations. Furthermore, considering other classical models used to describe the coupled dynamical processes, including the local awareness controlled contagion spreading (LACS) model, Susceptible-Infected-Susceptible-Unaware-Aware-Unaware (SIS-UAU) model and the single layer occasion, we make a detailed comparisons between the GACS with them. Although the comparisons and results depend on the parameters each model has, the GACS model always shows a strong restrain effects on epidemic spreading process. Our results give us a better understanding of the coupled dynamical processes and highlights the importance of considering the spreading of global awareness in the control of epidemics.

INTRODUCTION The global HIV epidemic continues to expand with ...

African Journals Online (AJOL)

maybe potentially dangerous in low resource settings.6. Women infected with ... The HIV epidemic in children parallels that among women on account of perinatal ... unknown.14, 15 Immune suppression resulting from general anaesthetics ...

Bilingual Language Control and General Purpose Cognitive Control among Individuals with Bilingual Aphasia: Evidence Based on Negative Priming and Flanker Tasks

Science.gov (United States)

Dash, Tanya; Kar, Bhoomika R.

2014-01-01

Background. Bilingualism results in an added advantage with respect to cognitive control. The interaction between bilingual language control and general purpose cognitive control systems can also be understood by studying executive control among individuals with bilingual aphasia. Objectives. The current study examined the subcomponents of cognitive control in bilingual aphasia. A case study approach was used to investigate whether cognitive control and language control are two separate systems and how factors related to bilingualism interact with control processes. Methods. Four individuals with bilingual aphasia performed a language background questionnaire, picture description task, and two experimental tasks (nonlinguistic negative priming task and linguistic and nonlinguistic versions of flanker task). Results. A descriptive approach was used to analyse the data using reaction time and accuracy measures. The cumulative distribution function plots were used to visualize the variations in performance across conditions. The results highlight the distinction between general purpose cognitive control and bilingual language control mechanisms. Conclusion. All participants showed predominant use of the reactive control mechanism to compensate for the limited resources system. Independent yet interactive systems for bilingual language control and general purpose cognitive control were postulated based on the experimental data derived from individuals with bilingual aphasia. PMID:24982591

Community Size Effects on Epidemic Spreading in Multiplex Social Networks.

Directory of Open Access Journals (Sweden)

Ting Liu

Full Text Available The dynamical process of epidemic spreading has drawn much attention of the complex network community. In the network paradigm, diseases spread from one person to another through the social ties amongst the population. There are a variety of factors that govern the processes of disease spreading on the networks. A common but not negligible factor is people's reaction to the outbreak of epidemics. Such reaction can be related information dissemination or self-protection. In this work, we explore the interactions between disease spreading and population response in terms of information diffusion and individuals' alertness. We model the system by mapping multiplex networks into two-layer networks and incorporating individuals' risk awareness, on the assumption that their response to the disease spreading depends on the size of the community they belong to. By comparing the final incidence of diseases in multiplex networks, we find that there is considerable mitigation of diseases spreading for full phase of spreading speed when individuals' protection responses are introduced. Interestingly, the degree of community overlap between the two layers is found to be critical factor that affects the final incidence. We also analyze the consequences of the epidemic incidence in communities with different sizes and the impacts of community overlap between two layers. Specifically, as the diseases information makes individuals alert and take measures to prevent the diseases, the effective protection is more striking in small community. These phenomena can be explained by the multiplexity of the networked system and the competition between two spreading processes.

Community Size Effects on Epidemic Spreading in Multiplex Social Networks.

Science.gov (United States)

Liu, Ting; Li, Ping; Chen, Yan; Zhang, Jie

2016-01-01

The dynamical process of epidemic spreading has drawn much attention of the complex network community. In the network paradigm, diseases spread from one person to another through the social ties amongst the population. There are a variety of factors that govern the processes of disease spreading on the networks. A common but not negligible factor is people's reaction to the outbreak of epidemics. Such reaction can be related information dissemination or self-protection. In this work, we explore the interactions between disease spreading and population response in terms of information diffusion and individuals' alertness. We model the system by mapping multiplex networks into two-layer networks and incorporating individuals' risk awareness, on the assumption that their response to the disease spreading depends on the size of the community they belong to. By comparing the final incidence of diseases in multiplex networks, we find that there is considerable mitigation of diseases spreading for full phase of spreading speed when individuals' protection responses are introduced. Interestingly, the degree of community overlap between the two layers is found to be critical factor that affects the final incidence. We also analyze the consequences of the epidemic incidence in communities with different sizes and the impacts of community overlap between two layers. Specifically, as the diseases information makes individuals alert and take measures to prevent the diseases, the effective protection is more striking in small community. These phenomena can be explained by the multiplexity of the networked system and the competition between two spreading processes.

Human mobility and time spent at destination: impact on spatial epidemic spreading.

Science.gov (United States)

Poletto, Chiara; Tizzoni, Michele; Colizza, Vittoria

2013-12-07

Host mobility plays a fundamental role in the spatial spread of infectious diseases. Previous theoretical works based on the integration of network theory into the metapopulation framework have shown that the heterogeneities that characterize real mobility networks favor the propagation of epidemics. Nevertheless, the studies conducted so far assumed the mobility process to be either Markovian (in which the memory of the origin of each traveler is lost) or non-Markovian with a fixed traveling time scale (in which individuals travel to a destination and come back at a constant rate). Available statistics however show that the time spent by travelers at destination is characterized by wide fluctuations, ranging from a single day up to several months. Such varying length of stay crucially affects the chance and duration of mixing events among hosts and may therefore have a strong impact on the spread of an emerging disease. Here, we present an analytical and a computational study of epidemic processes on a complex subpopulation network where travelers have memory of their origin and spend a heterogeneously distributed time interval at their destination. Through analytical calculations and numerical simulations we show that the heterogeneity of the length of stay alters the expression of the threshold between local outbreak and global invasion, and, moreover, it changes the epidemic behavior of the system in case of a global outbreak. Additionally, our theoretical framework allows us to study the effect of changes in the traveling behavior in response to the infection, by considering a scenario in which sick individuals do not leave their home location. Finally, we compare the results of our non-Markovian framework with those obtained with a classic Markovian approach and find relevant differences between the two, in the estimate of the epidemic invasion potential, as well as of the timing and the pattern of its spatial spread. These results highlight the importance of

Deciphering the Origin of the 2012 Cholera Epidemic in Guinea by Integrating Epidemiological and Molecular Analyses

Science.gov (United States)

Rebaudet, Stanislas; Mengel, Martin A.; Koivogui, Lamine; Moore, Sandra; Mutreja, Ankur; Kande, Yacouba; Yattara, Ousmane; Sarr Keita, Véronique; Njanpop-Lafourcade, Berthe-Marie; Fournier, Pierre-Edouard; Garnotel, Eric; Keita, Sakoba; Piarroux, Renaud

2014-01-01

Cholera is typically considered endemic in West Africa, especially in the Republic of Guinea. However, a three-year lull period was observed from 2009 to 2011, before a new epidemic struck the country in 2012, which was officially responsible for 7,350 suspected cases and 133 deaths. To determine whether cholera re-emerged from the aquatic environment or was rather imported due to human migration, a comprehensive epidemiological and molecular survey was conducted. A spatiotemporal analysis of the national case databases established Kaback Island, located off the southern coast of Guinea, as the initial focus of the epidemic in early February. According to the field investigations, the index case was found to be a fisherman who had recently arrived from a coastal district of neighboring Sierra Leone, where a cholera outbreak had recently occurred. MLVA-based genotype mapping of 38 clinical Vibrio cholerae O1 El Tor isolates sampled throughout the epidemic demonstrated a progressive genetic diversification of the strains from a single genotype isolated on Kaback Island in February, which correlated with spatial epidemic spread. Whole-genome sequencing characterized this strain as an “atypical” El Tor variant. Furthermore, genome-wide SNP-based phylogeny analysis grouped the Guinean strain into a new clade of the third wave of the seventh pandemic, distinct from previously analyzed African strains and directly related to a Bangladeshi isolate. Overall, these results highly suggest that the Guinean 2012 epidemic was caused by a V. cholerae clone that was likely imported from Sierra Leone by an infected individual. These results indicate the importance of promoting the cross-border identification and surveillance of mobile and vulnerable populations, including fishermen, to prevent, detect and control future epidemics in the region. Comprehensive epidemiological investigations should be expanded to better understand cholera dynamics and improve disease control

Modeling Epidemic Network Failures

DEFF Research Database (Denmark)

Ruepp, Sarah Renée; Fagertun, Anna Manolova

2013-01-01

This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... the SID model’s behavior and impact on the network performance, as well as the severity of the infection spreading. The simulations are carried out in OPNET Modeler. The model provides an important input to epidemic connection recovery mechanisms, and can due to its flexibility and versatility be used...... to evaluate multiple epidemic scenarios in various network types....

Predicting Subnational Ebola Virus Disease Epidemic Dynamics from Sociodemographic Indicators.

Directory of Open Access Journals (Sweden)

Linda Valeri

Full Text Available The recent Ebola virus disease (EVD outbreak in West Africa has spread wider than any previous human EVD epidemic. While individual-level risk factors that contribute to the spread of EVD have been studied, the population-level attributes of subnational regions associated with outbreak severity have not yet been considered.To investigate the area-level predictors of EVD dynamics, we integrated time series data on cumulative reported cases of EVD from the World Health Organization and covariate data from the Demographic and Health Surveys. We first estimated the early growth rates of epidemics in each second-level administrative district (ADM2 in Guinea, Sierra Leone and Liberia using exponential, logistic and polynomial growth models. We then evaluated how these growth rates, as well as epidemic size within ADM2s, were ecologically associated with several demographic and socio-economic characteristics of the ADM2, using bivariate correlations and multivariable regression models.The polynomial growth model appeared to best fit the ADM2 epidemic curves, displaying the lowest residual standard error. Each outcome was associated with various regional characteristics in bivariate models, however in stepwise multivariable models only mean education levels were consistently associated with a worse local epidemic.By combining two common methods-estimation of epidemic parameters using mathematical models, and estimation of associations using ecological regression models-we identified some factors predicting rapid and severe EVD epidemics in West African subnational regions. While care should be taken interpreting such results as anything more than correlational, we suggest that our approach of using data sources that were publicly available in advance of the epidemic or in real-time provides an analytic framework that may assist countries in understanding the dynamics of future outbreaks as they occur.

Retrospective Analysis of the 2014-2015 Ebola Epidemic in Liberia.

Science.gov (United States)

Atkins, Katherine E; Pandey, Abhishek; Wenzel, Natasha S; Skrip, Laura; Yamin, Dan; Nyenswah, Tolbert G; Fallah, Mosoka; Bawo, Luke; Medlock, Jan; Altice, Frederick L; Townsend, Jeffrey; Ndeffo-Mbah, Martial L; Galvani, Alison P

2016-04-01

The 2014-2015 Ebola epidemic has been the most protracted and devastating in the history of the disease. To prevent future outbreaks on this scale, it is imperative to understand the reasons that led to eventual disease control. Here, we evaluated the shifts of Ebola dynamics at national and local scales during the epidemic in Liberia. We used a transmission model calibrated to epidemiological data between June 9 and December 31, 2014, to estimate the extent of community and hospital transmission. We found that despite varied local epidemic patterns, community transmission was reduced by 40-80% in all the counties analyzed. Our model suggests that the tapering of the epidemic was achieved through reductions in community transmission, rather than accumulation of immune individuals through asymptomatic infection and unreported cases. Although the times at which this transmission reduction occurred in the majority of the Liberian counties started before any large expansion in hospital capacity and the distribution of home protection kits, it remains difficult to associate the presence of interventions with reductions in Ebola incidence. © The American Society of Tropical Medicine and Hygiene.

Epidemic Wave Dynamics Attributable to Urban Community Structure: A Theoretical Characterization of Disease Transmission in a Large Network

Science.gov (United States)

Eggo, Rosalind M; Lenczner, Michael

2015-01-01

Background Multiple waves of transmission during infectious disease epidemics represent a major public health challenge, but the ecological and behavioral drivers of epidemic resurgence are poorly understood. In theory, community structure—aggregation into highly intraconnected and loosely interconnected social groups—within human populations may lead to punctuated outbreaks as diseases progress from one community to the next. However, this explanation has been largely overlooked in favor of temporal shifts in environmental conditions and human behavior and because of the difficulties associated with estimating large-scale contact patterns. Objective The aim was to characterize naturally arising patterns of human contact that are capable of producing simulated epidemics with multiple wave structures. Methods We used an extensive dataset of proximal physical contacts between users of a public Wi-Fi Internet system to evaluate the epidemiological implications of an empirical urban contact network. We characterized the modularity (community structure) of the network and then estimated epidemic dynamics under a percolation-based model of infectious disease spread on the network. We classified simulated epidemics as multiwave using a novel metric and we identified network structures that were critical to the network’s ability to produce multiwave epidemics. Results We identified robust community structure in a large, empirical urban contact network from which multiwave epidemics may emerge naturally. This pattern was fueled by a special kind of insularity in which locally popular individuals were not the ones forging contacts with more distant social groups. Conclusions Our results suggest that ordinary contact patterns can produce multiwave epidemics at the scale of a single urban area without the temporal shifts that are usually assumed to be responsible. Understanding the role of community structure in epidemic dynamics allows officials to anticipate epidemic

Integrated travel network model for studying epidemics: Interplay between journeys and epidemic

Science.gov (United States)

Ruan, Zhongyuan; Wang, Chaoqing; Ming Hui, Pak; Liu, Zonghua

2015-06-01

The ease of travelling between cities has contributed much to globalization. Yet, it poses a threat on epidemic outbreaks. It is of great importance for network science and health control to understand the impact of frequent journeys on epidemics. We stress that a new framework of modelling that takes a traveller’s viewpoint is needed. Such integrated travel network (ITN) model should incorporate the diversity among links as dictated by the distances between cities and different speeds of different modes of transportation, diversity among nodes as dictated by the population and the ease of travelling due to infrastructures and economic development of a city, and round-trip journeys to targeted destinations via the paths of shortest travel times typical of human journeys. An example is constructed for 116 cities in China with populations over one million that are connected by high-speed train services and highways. Epidemic spread on the constructed network is studied. It is revealed both numerically and theoretically that the traveling speed and frequency are important factors of epidemic spreading. Depending on the infection rate, increasing the traveling speed would result in either an enhanced or suppressed epidemic, while increasing the traveling frequency enhances the epidemic spreading.

A Meta-Analysis of the Association between Gender and Protective Behaviors in Response to Respiratory Epidemics and Pandemics.

Science.gov (United States)

Moran, Kelly R; Del Valle, Sara Y

2016-01-01

Respiratory infectious disease epidemics and pandemics are recurring events that levy a high cost on individuals and society. The health-protective behavioral response of the public plays an important role in limiting respiratory infectious disease spread. Health-protective behaviors take several forms. Behaviors can be categorized as pharmaceutical (e.g., vaccination uptake, antiviral use) or non-pharmaceutical (e.g., hand washing, face mask use, avoidance of public transport). Due to the limitations of pharmaceutical interventions during respiratory epidemics and pandemics, public health campaigns aimed at limiting disease spread often emphasize both non-pharmaceutical and pharmaceutical behavioral interventions. Understanding the determinants of the public's behavioral response is crucial for devising public health campaigns, providing information to parametrize mathematical models, and ultimately limiting disease spread. While other reviews have qualitatively analyzed the body of work on demographic determinants of health-protective behavior, this meta-analysis quantitatively combines the results from 85 publications to determine the global relationship between gender and health-protective behavioral response. The results show that women in the general population are about 50% more likely than men to adopt/practice non-pharmaceutical behaviors. Conversely, men in the general population are marginally (about 12%) more likely than women to adopt/practice pharmaceutical behaviors. It is possible that factors other than pharmaceutical/non-pharmaceutical status not included in this analysis act as moderators of this relationship. These results suggest an inherent difference in how men and women respond to epidemic and pandemic respiratory infectious diseases. This information can be used to target specific groups when developing non-pharmaceutical public health campaigns and to parameterize epidemic models incorporating demographic information.

A Meta-Analysis of the Association between Gender and Protective Behaviors in Response to Respiratory Epidemics and Pandemics.

Directory of Open Access Journals (Sweden)

Kelly R Moran

Full Text Available Respiratory infectious disease epidemics and pandemics are recurring events that levy a high cost on individuals and society. The health-protective behavioral response of the public plays an important role in limiting respiratory infectious disease spread. Health-protective behaviors take several forms. Behaviors can be categorized as pharmaceutical (e.g., vaccination uptake, antiviral use or non-pharmaceutical (e.g., hand washing, face mask use, avoidance of public transport. Due to the limitations of pharmaceutical interventions during respiratory epidemics and pandemics, public health campaigns aimed at limiting disease spread often emphasize both non-pharmaceutical and pharmaceutical behavioral interventions. Understanding the determinants of the public's behavioral response is crucial for devising public health campaigns, providing information to parametrize mathematical models, and ultimately limiting disease spread. While other reviews have qualitatively analyzed the body of work on demographic determinants of health-protective behavior, this meta-analysis quantitatively combines the results from 85 publications to determine the global relationship between gender and health-protective behavioral response. The results show that women in the general population are about 50% more likely than men to adopt/practice non-pharmaceutical behaviors. Conversely, men in the general population are marginally (about 12% more likely than women to adopt/practice pharmaceutical behaviors. It is possible that factors other than pharmaceutical/non-pharmaceutical status not included in this analysis act as moderators of this relationship. These results suggest an inherent difference in how men and women respond to epidemic and pandemic respiratory infectious diseases. This information can be used to target specific groups when developing non-pharmaceutical public health campaigns and to parameterize epidemic models incorporating demographic information.

Individual-based modeling of fish: Linking to physical models and water quality.

Energy Technology Data Exchange (ETDEWEB)

Rose, K.A.

1997-08-01

The individual-based modeling approach for the simulating fish population and community dynamics is gaining popularity. Individual-based modeling has been used in many other fields, such as forest succession and astronomy. The popularity of the individual-based approach is partly a result of the lack of success of the more aggregate modeling approaches traditionally used for simulating fish population and community dynamics. Also, recent recognition that it is often the atypical individual that survives has fostered interest in the individual-based approach. Two general types of individual-based models are distribution and configuration. Distribution models follow the probability distributions of individual characteristics, such as length and age. Configuration models explicitly simulate each individual; the sum over individuals being the population. DeAngelis et al (1992) showed that, when distribution and configuration models were formulated from the same common pool of information, both approaches generated similar predictions. The distribution approach was more compact and general, while the configuration approach was more flexible. Simple biological changes, such as making growth rate dependent on previous days growth rates, were easy to implement in the configuration version but prevented simple analytical solution of the distribution version.

Cyber Epidemic Models with Dependences

OpenAIRE

Xu, Maochao; Da, Gaofeng; Xu, Shouhuai

2016-01-01

Studying models of cyber epidemics over arbitrary complex networks can deepen our understanding of cyber security from a whole-system perspective. In this paper, we initiate the investigation of cyber epidemic models that accommodate the {\\em dependences} between the cyber attack events. Due to the notorious difficulty in dealing with such dependences, essentially all existing cyber epidemic models have assumed them away. Specifically, we introduce the idea of Copulas into cyber epidemic mode...

Ebola hemorrhagic fever outbreaks: strategies for effective epidemic management, containment and control

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Gerald Amandu Matua

2015-05-01

The current epidemic management approaches are largely “reactive”, with containment efforts aimed at halting spread of existing outbreaks. We recommend that for better outcomes, in addition to “reactive” interventions, “pre-emptive” strategies also need to be instituted. We conclude that emphasizing both “reactive” and “pre-emptive” strategies is more likely to lead to better epidemic preparedness and response at individual, community, institutional, and government levels, resulting in timely containment of future Ebola outbreaks.

Multiple routes transmitted epidemics on multiplex networks

International Nuclear Information System (INIS)

Zhao, Dawei; Li, Lixiang; Peng, Haipeng; Luo, Qun; Yang, Yixian

2014-01-01

This letter investigates the multiple routes transmitted epidemic process on multiplex networks. We propose detailed theoretical analysis that allows us to accurately calculate the epidemic threshold and outbreak size. It is found that the epidemic can spread across the multiplex network even if all the network layers are well below their respective epidemic thresholds. Strong positive degree–degree correlation of nodes in multiplex network could lead to a much lower epidemic threshold and a relatively smaller outbreak size. However, the average similarity of neighbors from different layers of nodes has no obvious effect on the epidemic threshold and outbreak size. -- Highlights: •We studies multiple routes transmitted epidemic process on multiplex networks. •SIR model and bond percolation theory are used to analyze the epidemic processes. •We derive equations to accurately calculate the epidemic threshold and outbreak size. •ASN has no effect on the epidemic threshold and outbreak size. •Strong positive DDC leads to a lower epidemic threshold and a smaller outbreak size.

Multiple routes transmitted epidemics on multiplex networks

Energy Technology Data Exchange (ETDEWEB)

Zhao, Dawei [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Shandong Provincial Key Laboratory of Computer Network, Shandong Computer Science Center, Jinan 250014 (China); Li, Lixiang [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Peng, Haipeng, E-mail: penghaipeng@bupt.edu.cn [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Luo, Qun; Yang, Yixian [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China)

2014-02-01

This letter investigates the multiple routes transmitted epidemic process on multiplex networks. We propose detailed theoretical analysis that allows us to accurately calculate the epidemic threshold and outbreak size. It is found that the epidemic can spread across the multiplex network even if all the network layers are well below their respective epidemic thresholds. Strong positive degree–degree correlation of nodes in multiplex network could lead to a much lower epidemic threshold and a relatively smaller outbreak size. However, the average similarity of neighbors from different layers of nodes has no obvious effect on the epidemic threshold and outbreak size. -- Highlights: •We studies multiple routes transmitted epidemic process on multiplex networks. •SIR model and bond percolation theory are used to analyze the epidemic processes. •We derive equations to accurately calculate the epidemic threshold and outbreak size. •ASN has no effect on the epidemic threshold and outbreak size. •Strong positive DDC leads to a lower epidemic threshold and a smaller outbreak size.

Resource allocation for epidemic control in metapopulations.

Science.gov (United States)

Ndeffo Mbah, Martial L; Gilligan, Christopher A

2011-01-01

Deployment of limited resources is an issue of major importance for decision-making in crisis events. This is especially true for large-scale outbreaks of infectious diseases. Little is known when it comes to identifying the most efficient way of deploying scarce resources for control when disease outbreaks occur in different but interconnected regions. The policy maker is frequently faced with the challenge of optimizing efficiency (e.g. minimizing the burden of infection) while accounting for social equity (e.g. equal opportunity for infected individuals to access treatment). For a large range of diseases described by a simple SIRS model, we consider strategies that should be used to minimize the discounted number of infected individuals during the course of an epidemic. We show that when faced with the dilemma of choosing between socially equitable and purely efficient strategies, the choice of the control strategy should be informed by key measurable epidemiological factors such as the basic reproductive number and the efficiency of the treatment measure. Our model provides new insights for policy makers in the optimal deployment of limited resources for control in the event of epidemic outbreaks at the landscape scale.

Resource allocation for epidemic control in metapopulations.

Directory of Open Access Journals (Sweden)

Martial L Ndeffo Mbah

Full Text Available Deployment of limited resources is an issue of major importance for decision-making in crisis events. This is especially true for large-scale outbreaks of infectious diseases. Little is known when it comes to identifying the most efficient way of deploying scarce resources for control when disease outbreaks occur in different but interconnected regions. The policy maker is frequently faced with the challenge of optimizing efficiency (e.g. minimizing the burden of infection while accounting for social equity (e.g. equal opportunity for infected individuals to access treatment. For a large range of diseases described by a simple SIRS model, we consider strategies that should be used to minimize the discounted number of infected individuals during the course of an epidemic. We show that when faced with the dilemma of choosing between socially equitable and purely efficient strategies, the choice of the control strategy should be informed by key measurable epidemiological factors such as the basic reproductive number and the efficiency of the treatment measure. Our model provides new insights for policy makers in the optimal deployment of limited resources for control in the event of epidemic outbreaks at the landscape scale.

Social networks and spreading of epidemics

Science.gov (United States)

Trimper, Steffen; Zheng, Dafang; Brandau, Marian

2004-05-01

Epidemiological processes are studied within a recently proposed social network model using the susceptible-infected-refractory dynamics (SIR) of an epidemic. Within the network model, a population of individuals may be characterized by H independent hierarchies or dimensions, each of which consists of groupings of individuals into layers of subgroups. Detailed numerical simulations reveals that for H > 1, the global spreading results regardless of the degree of homophily α of the individuals forming a social circle. For H = 1, a transition from a global to a local spread occurs as the population becomes decomposed into increasingly homophilous groups. Multiple dimensions in classifying individuals (nodes) thus make a society (computer network) highly susceptible to large scale outbreaks of infectious diseases (viruses). The SIR-model can be extended by the inclusion of waiting times resulting in modified distribution function of the recovered.

Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance

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Sebastian Meyer

2017-05-01

Full Text Available The availability of geocoded health data and the inherent temporal structure of communicable diseases have led to an increased interest in statistical models and software for spatio-temporal data with epidemic features. The open source R package surveillance can handle various levels of aggregation at which infective events have been recorded: individual-level time-stamped geo-referenced data (case reports in either continuous space or discrete space, as well as counts aggregated by period and region. For each of these data types, the surveillance package implements tools for visualization, likelihoood inference and simulation from recently developed statistical regression frameworks capturing endemic and epidemic dynamics. Altogether, this paper is a guide to the spatio-temporal modeling of epidemic phenomena, exemplified by analyses of public health surveillance data on measles and invasive meningococcal disease.

What do young adults know about the HIV/AIDS epidemic? Findings from a population based study in Karachi, Pakistan.

Science.gov (United States)

Farid-ul-Hasnain, Syed; Johansson, Eva; Krantz, Gunilla

2009-03-26

HIVAIDS is spreading globally, hitting the younger generations. In Pakistan, the prevalence of HIV in high-risk subpopulations is five per cent or higher. This poses a serious threat of a generalised epidemic especially among the younger population. In the wake of HIVAIDS epidemic this is worrying as a well informed younger generation is crucial in restricting the spread of this epidemic. This study investigated Pakistani young adults' (male and female) knowledge and awareness of the HIV/AIDS disease. A population-based, cross-sectional study of 1,650 male and female adults aged 17-21 years living in Karachi was conducted using a structured questionnaire. A multi-stage cluster sampling design was used to collect data representative of the general population in an urban area. Bivariate and multivariate analyses were performed separately for males and females. Of 1,650 subjects, 24 per cent (n = 390) reported that they had not heard of HIV/AIDS. Among the males, those with a poor knowledge were younger (AOR = 2.20; 95 per cent CI, 1.38, 3.49), with less than six years of schooling (AOR = 2.46; 1.29 4.68) and no computer at home (AOR = 1.88; 1.06 3.34). Among the females, the risk factors for poor knowledge were young age (AOR = 1.74; 1.22, 2.50), low socio-economic status (AOR = 1.54; 1.06, 2.22), lack of enrolment at school/college (AOR = 1.61; 1.09, 2.39) and being unmarried (AOR = 1.85; 1.05, 3.26). Alarming gaps in knowledge relating to HIV/AIDS were detected. The study emphasises the need to educate young adults and equip them with the appropriate information and skills to enable them to protect themselves from HIV/AIDS. However, taboos surrounding public discussions of sexuality remain a key constraint to preventive activities.

Social and economic influences on human behavioural response in an emerging epidemic

Science.gov (United States)

Phang, P.; Wiwatanapataphee, B.; Wu, Y. H.

2017-10-01

The human behavioural changes have been recognized as an important key in shaping the disease spreading and determining the success of control measures in the course of epidemic outbreaks. However, apart from cost-benefit considerations, in reality, people are heterogeneous in their preferences towards adopting certain protective actions to reduce their risk of infection, and social norms have a function in individuals’ decision making. Here, we studied the interplay between the epidemic dynamics, imitation dynamics and the heterogeneity of individual protective behavioural response under the considerations of both economic and social factors, with a simple mathematical compartmental model and multi-population game dynamical replicator equations. We assume that susceptibles in different subpopulations have different preferences in adopting either normal or altered behaviour. By incorporating both intra- and inter-group social pressure, the outcome of the strategy distribution depends on the initial proportion of susceptible with normal and altered strategies in both subpopulations. The increase of additional cost to susceptible with altered behaviour will discourage people to take up protective actions and hence results in higher epidemic final size. For a specific cost of altered behaviour, the social group pressure could be a “double edge sword”, though. We conclude that the interplays between individual protective behaviour adoption, imitation and epidemic dynamics are necessarily complex if both economic and social factors act on populations with existing preferences.

Probing into the effectiveness of self-isolation policies in epidemic control

International Nuclear Information System (INIS)

Crokidakis, Nuno; Duarte Queirós, Sílvio M

2012-01-01

In this work, we inspect the reliability of controlling and quelling an epidemic disease mimicked by a susceptible–infected–susceptible (SIS) model defined on a complex network by means of current and implementable quarantine and isolation policies. Specifically, we consider that each individual in the network is originally linked to individuals of two types: members of the same household and acquaintances. The topology of this network evolves, taking into account a probability q that aims at representing the quarantine or isolation process in which the connection with acquaintances is severed according to standard policies of control of epidemics. Within current policies of self-isolation and standard infection rates, our results show that the propagation is either only controllable for hypothetical rates of compliance or not controllable at all

On the Use of Human Mobility Proxies for Modeling Epidemics

Science.gov (United States)

Tizzoni, Michele; Bajardi, Paolo; Decuyper, Adeline; Kon Kam King, Guillaume; Schneider, Christian M.; Blondel, Vincent; Smoreda, Zbigniew; González, Marta C.; Colizza, Vittoria

2014-01-01

Human mobility is a key component of large-scale spatial-transmission models of infectious diseases. Correctly modeling and quantifying human mobility is critical for improving epidemic control, but may be hindered by data incompleteness or unavailability. Here we explore the opportunity of using proxies for individual mobility to describe commuting flows and predict the diffusion of an influenza-like-illness epidemic. We consider three European countries and the corresponding commuting networks at different resolution scales, obtained from (i) official census surveys, (ii) proxy mobility data extracted from mobile phone call records, and (iii) the radiation model calibrated with census data. Metapopulation models defined on these countries and integrating the different mobility layers are compared in terms of epidemic observables. We show that commuting networks from mobile phone data capture the empirical commuting patterns well, accounting for more than 87% of the total fluxes. The distributions of commuting fluxes per link from mobile phones and census sources are similar and highly correlated, however a systematic overestimation of commuting traffic in the mobile phone data is observed. This leads to epidemics that spread faster than on census commuting networks, once the mobile phone commuting network is considered in the epidemic model, however preserving to a high degree the order of infection of newly affected locations. Proxies' calibration affects the arrival times' agreement across different models, and the observed topological and traffic discrepancies among mobility sources alter the resulting epidemic invasion patterns. Results also suggest that proxies perform differently in approximating commuting patterns for disease spread at different resolution scales, with the radiation model showing higher accuracy than mobile phone data when the seed is central in the network, the opposite being observed for peripheral locations. Proxies should therefore be

Effective degree Markov-chain approach for discrete-time epidemic processes on uncorrelated networks.

Science.gov (United States)

Cai, Chao-Ran; Wu, Zhi-Xi; Guan, Jian-Yue

2014-11-01

Recently, Gómez et al. proposed a microscopic Markov-chain approach (MMCA) [S. Gómez, J. Gómez-Gardeñes, Y. Moreno, and A. Arenas, Phys. Rev. E 84, 036105 (2011)PLEEE81539-375510.1103/PhysRevE.84.036105] to the discrete-time susceptible-infected-susceptible (SIS) epidemic process and found that the epidemic prevalence obtained by this approach agrees well with that by simulations. However, we found that the approach cannot be straightforwardly extended to a susceptible-infected-recovered (SIR) epidemic process (due to its irreversible property), and the epidemic prevalences obtained by MMCA and Monte Carlo simulations do not match well when the infection probability is just slightly above the epidemic threshold. In this contribution we extend the effective degree Markov-chain approach, proposed for analyzing continuous-time epidemic processes [J. Lindquist, J. Ma, P. Driessche, and F. Willeboordse, J. Math. Biol. 62, 143 (2011)JMBLAJ0303-681210.1007/s00285-010-0331-2], to address discrete-time binary-state (SIS) or three-state (SIR) epidemic processes on uncorrelated complex networks. It is shown that the final epidemic size as well as the time series of infected individuals obtained from this approach agree very well with those by Monte Carlo simulations. Our results are robust to the change of different parameters, including the total population size, the infection probability, the recovery probability, the average degree, and the degree distribution of the underlying networks.

Retrospective Analysis of the 2014–2015 Ebola Epidemic in Liberia

Science.gov (United States)

Atkins, Katherine E.; Pandey, Abhishek; Wenzel, Natasha S.; Skrip, Laura; Yamin, Dan; Nyenswah, Tolbert G.; Fallah, Mosoka; Bawo, Luke; Medlock, Jan; Altice, Frederick L.; Townsend, Jeffrey; Ndeffo-Mbah, Martial L.; Galvani, Alison P.

2016-01-01

The 2014–2015 Ebola epidemic has been the most protracted and devastating in the history of the disease. To prevent future outbreaks on this scale, it is imperative to understand the reasons that led to eventual disease control. Here, we evaluated the shifts of Ebola dynamics at national and local scales during the epidemic in Liberia. We used a transmission model calibrated to epidemiological data between June 9 and December 31, 2014, to estimate the extent of community and hospital transmission. We found that despite varied local epidemic patterns, community transmission was reduced by 40–80% in all the counties analyzed. Our model suggests that the tapering of the epidemic was achieved through reductions in community transmission, rather than accumulation of immune individuals through asymptomatic infection and unreported cases. Although the times at which this transmission reduction occurred in the majority of the Liberian counties started before any large expansion in hospital capacity and the distribution of home protection kits, it remains difficult to associate the presence of interventions with reductions in Ebola incidence. PMID:26928839

Viral conductance : Quantifying the robustness of networks with respect to spread of epidemics

NARCIS (Netherlands)

Youssef, M.; Kooij, R.E.; Scoglio, C.

2011-01-01

In this paper, we propose a novel measure, viral conductance (VC), to assess the robustness of complex networks with respect to the spread of SIS epidemics. In contrast to classical measures that assess the robustness of networks based on the epidemic threshold above which an epidemic takes place,

Alcohol dependence and physical comorbidity: Increased prevalence but reduced relevance of individual comorbidities for hospital-based mortality during a 12.5-year observation period in general hospital admissions in urban North-West England.

Science.gov (United States)

Schoepf, D; Heun, R

2015-06-01

Alcohol dependence (AD) is associated with an increase in physical comorbidities. The effects of these diseases on general hospital-based mortality are unclear. Consequently, we conducted a mortality study in which we investigated if the burden of physical comorbidities and their relevance on general hospital-based mortality differs between individuals with and without AD during a 12.5-year observation period in general hospital admissions. During 1 January 2000 and 30 June 2012, 23,371 individuals with AD were admitted at least once to seven General Manchester Hospitals. Their physical comorbidities with a prevalence≥1% were compared to those of 233,710 randomly selected hospital controls, group-matched for age and gender (regardless of primary admission diagnosis or specialized treatments). Physical comorbidities that increased the risk of hospital-based mortality (but not outside of the hospital) during the observation period were identified using multiple logistic regression analyses. Hospital-based mortality rates were 20.4% in the AD sample and 8.3% in the control sample. Individuals with AD compared to controls had a higher burden of physical comorbidities, i.e. alcoholic liver and pancreatic diseases, diseases of the conducting airways, neurological and circulatory diseases, diseases of the upper gastrointestinal tract, renal diseases, cellulitis, iron deficiency anemia, fracture neck of femur, and peripheral vascular disease. In contrast, coronary heart related diseases, risk factors of cardiovascular disease, diverticular disease and cataracts were less frequent in individuals with AD than in controls. Thirty-two individual physical comorbidities contributed to the prediction of hospital-based mortality in univariate analyses in the AD sample; alcoholic liver disease (33.7%), hypertension (16.9%), chronic obstructive pulmonary disease (14.1%), and pneumonia (13.3%) were the most frequent diagnoses in deceased individuals with AD. Multiple forward

Economic cost and burden of dengue during epidemics and non-epidemic years in Taiwan

Directory of Open Access Journals (Sweden)

Dih-Ling Luh

2018-03-01

Full Text Available Background: Determining the disease and economic burden of dengue is critical for the allocation of public health resources. Several studies have used disability-adjusted life-years (DALYs to estimate the disease burden of dengue in different regions. However, there are no published studies discussing the estimates of dengue-related economic and disease burden specifically in Taiwan. Objectives: We assessed the economic cost and disease burden of dengue infections in Taiwan for the period 1998–2014, and compared these during epidemic and non-epidemic years. Methods: We estimated the annual DALYs per million population using the disability weights for dengue fever (DF, dengue hemorrhagic fever (DHF, dengue shock syndrome (DSS, and death cases. Economic costs were estimated and divided into direct (medical costs and indirect costs (lost work days and caregiver fees. Results: For the period 1998–2014, a mean of 115.3 (range: 6.3–934.3 DALYs per million population annually were lost to dengue. In epidemic years, direct costs associated with dengue resulted mostly from hospitalization (86.09%, emergency (7.77%, outpatient (6.10%, and drug costs (0.03%. For indirect costs, lost productivity due to death (70.76% was the dominant contributor. Overall, the costs were 12.3 times higher in epidemic years than in non-epidemic years (Wilcoxon rank sum test, p < 0.05. Conclusions: This study is the first to evaluate the economic costs and disease burden of dengue infections for this period in Taiwan, and reveals significant differences in economic impact between epidemic and non-epidemic years. Keywords: Economic cost of disease, Disease burden, Disability-adjusted life years (DALYs, Dengue, Epidemic

Prevalence of cutaneous leishmaniasis along the Nile River north of Khartoum (Sudan) in the aftermath of an epidemic in 1985

DEFF Research Database (Denmark)

Kadaro, A Y; Ghalib, H W; Ali, M S

1993-01-01

Based on a pilot clinical study of the prevalence of cutaneous leishmaniasis (CL) among school children in villages on both banks of the Nile River north of Khartoum, Sudan in the aftermath of a 1985 epidemic, we studied a random sample (303 individuals) from one of these villages to determine...

Global HIV/AIDS Epidemic

Science.gov (United States)

... Policy The Global HIV/AIDS Epidemic The Global HIV/AIDS Epidemic Published: Nov 29, 2017 Facebook Twitter ... 2001-FY 2018 Request The Global Response to HIV/AIDS International efforts to combat HIV began in ...

Inter-epidemic acquisition of Rift Valley fever virus in humans in Tanzania.

Directory of Open Access Journals (Sweden)

Robert David Sumaye

2015-02-01

Full Text Available BACKGROUND: In East Africa, epidemics of Rift Valley fever (RVF occur in cycles of 5-15 years following unusually high rainfall. RVF transmission during inter-epidemic periods (IEP generally passes undetected in absence of surveillance in mammalian hosts and vectors. We studied IEP transmission of RVF and evaluated the demographic, behavioural, occupational and spatial determinants of past RVF infection. METHODOLOGY: Between March and August 2012 we collected blood samples, and administered a risk factor questionnaire among 606 inhabitants of 6 villages in the seasonally inundated Kilombero Valley, Tanzania. ELISA tests were used to detect RVFV IgM and IgG antibodies in serum samples. Risk factors were examined by mixed effects logistic regression. FINDINGS: RVF virus IgM antibodies, indicating recent RVFV acquisition, were detected in 16 participants, representing 2.6% overall and in 22.5% of inhibition ELISA positives (n = 71. Four of 16 (25.0% IgM positives and 11/71 (15.5% of individuals with inhibition ELISA sero-positivity reported they had had no previous contact with host animals. Sero-positivity on inhibition ELISA was 11.7% (95% CI 9.2-14.5 and risk was elevated with age (odds ratio (OR 1.03 per year; 95% CI 1.01-1.04, among milkers (OR 2.19; 95% CI 1.23-3.91, and individuals eating raw meat (OR 4.17; 95% CI 1.18-14.66. Households keeping livestock had a higher probability of having members with evidence of past infection (OR = 3.04, 95% CI = 1.42-6.48 than those that do not keep livestock. CONCLUSION: There is inter-epidemic acquisition of RVFV in Kilombero Valley inhabitants. In the wake of declining malaria incidence, these findings underscore the need for clinicians to consider RVF in the differential diagnosis for febrile illnesses. Several types of direct contact with livestock are important risk factors for past infection with RVFV in this study's population. However, at least part of RVFV transmission appears to have occurred

Epidemic modeling in complex realities.

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Colizza, Vittoria; Barthélemy, Marc; Barrat, Alain; Vespignani, Alessandro

2007-04-01

In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.

Population-based strategies to control manufacturing epidemics.

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Gorini, Giuseppe

2017-01-01

"The multinational corporations producing tobacco, alcohol, soft drinks, and processed foods have a role of vectors in the increase of chronic diseases, so that one can speak of manufacturing epidemics. The main aim of this paper is to conduct a literature review on different approaches in population-based interventions to stem the rise in consumption of unhealthy products. Different approaches were found: • command-and-control regulations: the route is definitely more advanced for tobacco with the implementation of an international treaty, which requires 180 ratifying states to implement a series of tobacco control policies. Similar regulations have been partially adopted to reduce alcohol use and to increase taxes of sugar-sweetened beverages; • multinational corporations in few Countries can voluntarily adopt recommendations on media campaigns and on labelling of soft drinks and processed foods; • in order to reduce salt in foods, many Countries developed voluntary agreements with industries with monitoring systems to assess compliance. Population-based interventions to try to align the interests of multinational corporations with those of public health are described in literature: • the "Health Footprint" programme; • the performance-based regulation which could oblige industry to take responsibility to reduce the harmful consequences of the use of their unhealthy commodities; • the price-cap regulation, usually applied to the utilities sector, would set a cap on the price of the tobacco industry, raising the tobacco taxes by 500 million euros per year. In order to reduce the burden of chronic disease, one of the objectives of the Italian National Prevention Plan, a working group including non-governmental organizations and experts in communication, social marketing, and lifestyles should be organized by the Ministry of Health in order to identify which population-based interventions could be implemented in Italy in next years to stem the rise of

Epidemic spreading in multiplex networks influenced by opinion exchanges on vaccination.

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Alvarez-Zuzek, Lucila G; La Rocca, Cristian E; Iglesias, José R; Braunstein, Lidia A

2017-01-01

Through years, the use of vaccines has always been a controversial issue. People in a society may have different opinions about how beneficial the vaccines are and as a consequence some of those individuals decide to vaccinate or not themselves and their relatives. This attitude in face of vaccines has clear consequences in the spread of diseases and their transformation in epidemics. Motivated by this scenario, we study, in a simultaneous way, the changes of opinions about vaccination together with the evolution of a disease. In our model we consider a multiplex network consisting of two layers. One of the layers corresponds to a social network where people share their opinions and influence others opinions. The social model that rules the dynamic is the M-model, which takes into account two different processes that occurs in a society: persuasion and compromise. This two processes are related through a parameter r, r 1 the society tends to have extremist opinions, while r = 1 represents a neutral society. This social network may be of real or virtual contacts. On the other hand, the second layer corresponds to a network of physical contacts where the disease spreading is described by the SIR-Model. In this model the individuals may be in one of the following four states: Susceptible (S), Infected(I), Recovered (R) or Vaccinated (V). A Susceptible individual can: i) get vaccinated, if his opinion in the other layer is totally in favor of the vaccine, ii) get infected, with probability β if he is in contact with an infected neighbor. Those I individuals recover after a certain period tr = 6. Vaccinated individuals have an extremist positive opinion that does not change. We consider that the vaccine has a certain effectiveness ω and as a consequence vaccinated nodes can be infected with probability β(1 - ω) if they are in contact with an infected neighbor. In this case, if the infection process is successful, the new infected individual changes his opinion from

Epidemic spreading in multiplex networks influenced by opinion exchanges on vaccination.

Directory of Open Access Journals (Sweden)

Lucila G Alvarez-Zuzek

Full Text Available Through years, the use of vaccines has always been a controversial issue. People in a society may have different opinions about how beneficial the vaccines are and as a consequence some of those individuals decide to vaccinate or not themselves and their relatives. This attitude in face of vaccines has clear consequences in the spread of diseases and their transformation in epidemics. Motivated by this scenario, we study, in a simultaneous way, the changes of opinions about vaccination together with the evolution of a disease. In our model we consider a multiplex network consisting of two layers. One of the layers corresponds to a social network where people share their opinions and influence others opinions. The social model that rules the dynamic is the M-model, which takes into account two different processes that occurs in a society: persuasion and compromise. This two processes are related through a parameter r, r 1 the society tends to have extremist opinions, while r = 1 represents a neutral society. This social network may be of real or virtual contacts. On the other hand, the second layer corresponds to a network of physical contacts where the disease spreading is described by the SIR-Model. In this model the individuals may be in one of the following four states: Susceptible (S, Infected(I, Recovered (R or Vaccinated (V. A Susceptible individual can: i get vaccinated, if his opinion in the other layer is totally in favor of the vaccine, ii get infected, with probability β if he is in contact with an infected neighbor. Those I individuals recover after a certain period tr = 6. Vaccinated individuals have an extremist positive opinion that does not change. We consider that the vaccine has a certain effectiveness ω and as a consequence vaccinated nodes can be infected with probability β(1 - ω if they are in contact with an infected neighbor. In this case, if the infection process is successful, the new infected individual changes his

Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system

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Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-10-01

Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

Impacts of clustering on interacting epidemics.

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Wang, Bing; Cao, Lang; Suzuki, Hideyuki; Aihara, Kazuyuki

2012-07-07

Since community structures in real networks play a major role for the epidemic spread, we therefore explore two interacting diseases spreading in networks with community structures. As a network model with community structures, we propose a random clique network model composed of different orders of cliques. We further assume that each disease spreads only through one type of cliques; this assumption corresponds to the issue that two diseases spread inside communities and outside them. Considering the relationship between the susceptible-infected-recovered (SIR) model and the bond percolation theory, we apply this theory to clique random networks under the assumption that the occupation probability is clique-type dependent, which is consistent with the observation that infection rates inside a community and outside it are different, and obtain a number of statistical properties for this model. Two interacting diseases that compete the same hosts are also investigated, which leads to a natural generalization of analyzing an arbitrary number of infectious diseases. For two-disease dynamics, the clustering effect is hypersensitive to the cohesiveness and concentration of cliques; this illustrates the impacts of clustering and the composition of subgraphs in networks on epidemic behavior. The analysis of coexistence/bistability regions provides significant insight into the relationship between the network structure and the potential epidemic prevalence. Copyright © 2012 Elsevier Ltd. All rights reserved.

Differences in diagnostic activity in general practice and findings for individuals invited to the danish screening programme for colorectal cancer: a population-based cohort study.

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Juul, Jakob Søgaard; Andersen, Berit; Laurberg, Søren; Carlsen, Anders Helles; Olesen, Frede; Vedsted, Peter

2018-06-22

To investigate the diagnostic activity in general practice and the cumulative incidence of colorectal cancer (CRC) in individuals invited to the Danish national screening programme for CRC. A historical population-based cohort study. The Danish CRC screening programme and general practice. The 376,198 individuals invited to the Danish CRC screening programme from 1 March to 31 December 2014. The diagnostic activity (consultations and haemoglobin measures) in general practice in the year preceding the screening invitation and the cumulated incidence of CRC in the year following the screening invitation. Screening participants had significantly higher diagnostic activity than non-participants. Individuals with a positive faecal immunochemical test (FIT) had higher diagnostic activity compared to individuals with a negative FIT, and a small increase in the months leading up to the invitation. Individuals with a screen-detected CRC had lower diagnostic activity than individuals with no CRC. In total, 308 (25.3%) of CRCs diagnosed in the invited population were diagnosed outside the screening programme. Non-participants with CRC more often had low socio-economic status, high comorbidity and stage IV CRC than participants with CRC. There was a tendency that participants and those with a positive FIT had a higher diagnostic activity the year before the screening. This was not seen for those with CRC detected through screening. CRC must still be diagnosed in general practice in the invited population and non-participants are of special interest as they have higher risk of late stage CRC. Key Points Current awareness:Individuals with colorectal cancer (CRC) in screening may be symptomatic and CRC may still occur outside screening in the invited population. Most important points:The majority of individuals with CRC in screening cannot be expected to be diagnosed on symptomatic presentation in general practice GPs have to be aware that CRC still occurs outside screening in

The chemical bases of the various AIDS epidemics: recreational ...

Indian Academy of Sciences (India)

Why did AIDS not rise and then decline exponentially owing to antiviral immunity like all other viral epidemics? Why is AIDS not contagious? Why would only HIV carriers get AIDS who use either recreational or anti-HIV drugs or are subject to malnutrition? Why is the mortality of HIV-antibody-positives treated with anti-HIV ...

Epidemic spreading in weighted scale-free networks with community structure

International Nuclear Information System (INIS)

Chu, Xiangwei; Guan, Jihong; Zhang, Zhongzhi; Zhou, Shuigeng

2009-01-01

Many empirical studies reveal that the weights and community structure are ubiquitous in various natural and artificial networks. In this paper, based on the SI disease model, we investigate the epidemic spreading in weighted scale-free networks with community structure. Two exponents, α and β, are introduced to weight the internal edges and external edges, respectively; and a tunable probability parameter q is also introduced to adjust the strength of community structure. We find the external weighting exponent β plays a much more important role in slackening the epidemic spreading and reducing the danger brought by the epidemic than the internal weighting exponent α. Moreover, a novel result we find is that the strong community structure is no longer helpful for slackening the danger brought by the epidemic in the weighted cases. In addition, we show the hierarchical dynamics of the epidemic spreading in the weighted scale-free networks with communities which is also displayed in the famous BA scale-free networks

Getting to grips with the obesity epidemic in Europe

Directory of Open Access Journals (Sweden)

Sarah Cuschieri

2016-09-01

Full Text Available Obesity is a global epidemic. It is responsible for increased patient morbidity and mortality. Significant related pathologies including diabetes mellitus compound the overall risks. Obesity is a significant financial burden. This includes direct and indirect medical costs, amounting to millions of euros each year. Multiple European studies have outlined a steady incline in obesity prevalence rates. Tackling obesity is no easy task. Policy makers aiming to reduce obesity rates should adopt an evidence-based approach. This entails adopting both micro- and macro-interventions tweaked to each country’s individual requirements. The ideal way forward would be to tackle obesity from the individual, population-wide and food industry angles. The key towards a successful intervention is for each country to carry out well-planned health examination studies, in an attempt to pin point local risk factors. Having a correct individualized picture, each country can move forward and draw policies and interventional procedures. The aim should be to primarily improve the quality of life. Second, the country’s capital expenditure is also reduced.

Sequential detection of influenza epidemics by the Kolmogorov-Smirnov test

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Closas Pau

2012-10-01

Full Text Available Abstract Background Influenza is a well known and common human respiratory infection, causing significant morbidity and mortality every year. Despite Influenza variability, fast and reliable outbreak detection is required for health resource planning. Clinical health records, as published by the Diagnosticat database in Catalonia, host useful data for probabilistic detection of influenza outbreaks. Methods This paper proposes a statistical method to detect influenza epidemic activity. Non-epidemic incidence rates are modeled against the exponential distribution, and the maximum likelihood estimate for the decaying factor λ is calculated. The sequential detection algorithm updates the parameter as new data becomes available. Binary epidemic detection of weekly incidence rates is assessed by Kolmogorov-Smirnov test on the absolute difference between the empirical and the cumulative density function of the estimated exponential distribution with significance level 0 ≤ α ≤ 1. Results The main advantage with respect to other approaches is the adoption of a statistically meaningful test, which provides an indicator of epidemic activity with an associated probability. The detection algorithm was initiated with parameter λ0 = 3.8617 estimated from the training sequence (corresponding to non-epidemic incidence rates of the 2008-2009 influenza season and sequentially updated. Kolmogorov-Smirnov test detected the following weeks as epidemic for each influenza season: 50−10 (2008-2009 season, 38−50 (2009-2010 season, weeks 50−9 (2010-2011 season and weeks 3 to 12 for the current 2011-2012 season. Conclusions Real medical data was used to assess the validity of the approach, as well as to construct a realistic statistical model of weekly influenza incidence rates in non-epidemic periods. For the tested data, the results confirmed the ability of the algorithm to detect the start and the end of epidemic periods. In general, the proposed test could

Hepatitis E epidemics in India

Indian Academy of Sciences (India)

The first well recorded epidemic was in 1955-56 here in Delhi with nearly 30000 cases. Large outbreaks occurred in 1978 in Kashmir. My interest in this disease began in 1991 during investigations into a large epidemic of hepatitis E in Kanpur that my mentor, later Prof SR Naik, and I undertook. I will use this epidemic as an ...

Heroin epidemics, treatment and ODE modelling.

Science.gov (United States)

White, Emma; Comiskey, Catherine

2007-07-01

The UN [United Nations Office on Drugs and Crime (UNODC): World Drug Report, 2005, vol. 1: Analysis. UNODC, 2005.], EU [European Monitoring Centre for Drugs and Drug Addiction (EMCDDA): Annual Report, 2005.http://annualreport.emcdda.eu.int/en/home-en.html.] and WHO [World Health Organisation (WHO): Biregional Strategy for Harm Reduction, 2005-2009. HIV and Injecting Drug Use. WHO, 2005.] have consistently highlighted in recent years the ongoing and persistent nature of opiate and particularly heroin use on a global scale. While this is a global phenomenon, authors have emphasised the significant impact such an epidemic has on individual lives and on society. National prevalence studies have indicated the scale of the problem, but the drug-using career, typically consisting of initiation, habitual use, a treatment-relapse cycle and eventual recovery, is not well understood. This paper presents one of the first ODE models of opiate addiction, based on the principles of mathematical epidemiology. The aim of this model is to identify parameters of interest for further study, with a view to informing and assisting policy-makers in targeting prevention and treatment resources for maximum effectiveness. An epidemic threshold value, R(0), is proposed for the drug-using career. Sensitivity analysis is performed on R(0) and it is then used to examine the stability of the system. A condition under which a backward bifurcation may exist is found, as are conditions that permit the existence of one or more endemic equilibria. A key result arising from this model is that prevention is indeed better than cure.

Epidemic genital retraction syndrome: environmental and personal risk factors in southern China.

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Cheng, S T

1997-01-01

Koro is the term used to define the fear that one's sex organ is retracting into the body and that the complete retraction of the organ will result in death. While koro is found mainly among the Chinese and other Asian societies near China, the condition is most prevalent in southern China, where repeated epidemics have occurred. In that region, koro is found only among the Hans, the dominant ethnic group, and is over-represented among people under age 24 years. Koro provokes considerable anxiety in the individual in question and his/her family and neighbors, and is more prevalent among males than females. Men try to pull the penis out from the body or to prevent it from shrinking further by tying a string around the penis or securing it with a clamping device. Some Asian women have reported shrinking breasts, nipples, or labia. Relatives and neighbors of the same sex often help to rescue the organ in question, especially in applying anchoring devices. Others may also believe a person has koro and attempt to rescue their organ without the individual's consent. Injury to the sex organ, including bruises, bleeding, and infection, is common and sometimes results in permanent damage. In general, however, koro attacks are acute, brief, and tend not to recur. The 1984-85 koro epidemic in Hainan Island and Leizhou Peninsula is reviewed to shed light upon prevailing cultural attitudes and beliefs, news and rumors about koro, and anxiety in neighborhoods which may be causative environmental risk factors for koro. Education, age, and marital status are considered as individual risk factors. Koro in China is best described as a social sickness supported by cultural myths which tend to affect young people who are deprived of proper sex information to explain their physical development.

Individual-based ecology of coastal birds.

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Stillman, Richard A; Goss-Custard, John D

2010-08-01

Conservation objectives for non-breeding coastal birds (shorebirds and wildfowl) are determined from their population size at coastal sites. To advise coastal managers, models must predict quantitatively the effects of environmental change on population size or the demographic rates (mortality and reproduction) that determine it. As habitat association models and depletion models are not able to do this, we developed an approach that has produced such predictions thereby enabling policy makers to make evidence-based decisions. Our conceptual framework is individual-based ecology, in which populations are viewed as having properties (e.g. size) that arise from the traits (e.g. behaviour, physiology) and interactions of their constituent individuals. The link between individuals and populations is made through individual-based models (IBMs) that follow the fitness-maximising decisions of individuals and predict population-level consequences (e.g. mortality rate) from the fates of these individuals. Our first IBM was for oystercatchers Haematopus ostralegus and accurately predicted their density-dependent mortality. Subsequently, IBMs were developed for several shorebird and wildfowl species at several European sites, and were shown to predict accurately overwinter mortality, and the foraging behaviour from which predictions are derived. They have been used to predict the effect on survival in coastal birds of sea level rise, habitat loss, wind farm development, shellfishing and human disturbance. This review emphasises the wider applicability of the approach, and identifies other systems to which it could be applied. We view the IBM approach as a very useful contribution to the general problem of how to advance ecology to the point where we can routinely make meaningful predictions of how populations respond to environmental change.

Characterizing the reproduction number of epidemics with early subexponential growth dynamics.

Science.gov (United States)

Chowell, Gerardo; Viboud, Cécile; Simonsen, Lone; Moghadas, Seyed M

2016-10-01

Early estimates of the transmission potential of emerging and re-emerging infections are increasingly used to inform public health authorities on the level of risk posed by outbreaks. Existing methods to estimate the reproduction number generally assume exponential growth in case incidence in the first few disease generations, before susceptible depletion sets in. In reality, outbreaks can display subexponential (i.e. polynomial) growth in the first few disease generations, owing to clustering in contact patterns, spatial effects, inhomogeneous mixing, reactive behaviour changes or other mechanisms. Here, we introduce the generalized growth model to characterize the early growth profile of outbreaks and estimate the effective reproduction number, with no need for explicit assumptions about the shape of epidemic growth. We demonstrate this phenomenological approach using analytical results and simulations from mechanistic models, and provide validation against a range of empirical disease datasets. Our results suggest that subexponential growth in the early phase of an epidemic is the rule rather the exception. Mechanistic simulations show that slight modifications to the classical susceptible-infectious-removed model result in subexponential growth, and in turn a rapid decline in the reproduction number within three to five disease generations. For empirical outbreaks, the generalized-growth model consistently outperforms the exponential model for a variety of directly and indirectly transmitted diseases datasets (pandemic influenza, measles, smallpox, bubonic plague, cholera, foot-and-mouth disease, HIV/AIDS and Ebola) with model estimates supporting subexponential growth dynamics. The rapid decline in effective reproduction number predicted by analytical results and observed in real and synthetic datasets within three to five disease generations contrasts with the expectation of invariant reproduction number in epidemics obeying exponential growth. The

Characterizing the reproduction number of epidemics with early subexponential growth dynamics

Science.gov (United States)

Viboud, Cécile; Simonsen, Lone; Moghadas, Seyed M.

2016-01-01

Early estimates of the transmission potential of emerging and re-emerging infections are increasingly used to inform public health authorities on the level of risk posed by outbreaks. Existing methods to estimate the reproduction number generally assume exponential growth in case incidence in the first few disease generations, before susceptible depletion sets in. In reality, outbreaks can display subexponential (i.e. polynomial) growth in the first few disease generations, owing to clustering in contact patterns, spatial effects, inhomogeneous mixing, reactive behaviour changes or other mechanisms. Here, we introduce the generalized growth model to characterize the early growth profile of outbreaks and estimate the effective reproduction number, with no need for explicit assumptions about the shape of epidemic growth. We demonstrate this phenomenological approach using analytical results and simulations from mechanistic models, and provide validation against a range of empirical disease datasets. Our results suggest that subexponential growth in the early phase of an epidemic is the rule rather the exception. Mechanistic simulations show that slight modifications to the classical susceptible–infectious–removed model result in subexponential growth, and in turn a rapid decline in the reproduction number within three to five disease generations. For empirical outbreaks, the generalized-growth model consistently outperforms the exponential model for a variety of directly and indirectly transmitted diseases datasets (pandemic influenza, measles, smallpox, bubonic plague, cholera, foot-and-mouth disease, HIV/AIDS and Ebola) with model estimates supporting subexponential growth dynamics. The rapid decline in effective reproduction number predicted by analytical results and observed in real and synthetic datasets within three to five disease generations contrasts with the expectation of invariant reproduction number in epidemics obeying exponential growth. The

FluBreaks: early epidemic detection from Google flu trends.

Science.gov (United States)

Pervaiz, Fahad; Pervaiz, Mansoor; Abdur Rehman, Nabeel; Saif, Umar

2012-10-04

The Google Flu Trends service was launched in 2008 to track changes in the volume of online search queries related to flu-like symptoms. Over the last few years, the trend data produced by this service has shown a consistent relationship with the actual number of flu reports collected by the US Centers for Disease Control and Prevention (CDC), often identifying increases in flu cases weeks in advance of CDC records. However, contrary to popular belief, Google Flu Trends is not an early epidemic detection system. Instead, it is designed as a baseline indicator of the trend, or changes, in the number of disease cases. To evaluate whether these trends can be used as a basis for an early warning system for epidemics. We present the first detailed algorithmic analysis of how Google Flu Trends can be used as a basis for building a fully automated system for early warning of epidemics in advance of methods used by the CDC. Based on our work, we present a novel early epidemic detection system, called FluBreaks (dritte.org/flubreaks), based on Google Flu Trends data. We compared the accuracy and practicality of three types of algorithms: normal distribution algorithms, Poisson distribution algorithms, and negative binomial distribution algorithms. We explored the relative merits of these methods, and related our findings to changes in Internet penetration and population size for the regions in Google Flu Trends providing data. Across our performance metrics of percentage true-positives (RTP), percentage false-positives (RFP), percentage overlap (OT), and percentage early alarms (EA), Poisson- and negative binomial-based algorithms performed better in all except RFP. Poisson-based algorithms had average values of 99%, 28%, 71%, and 76% for RTP, RFP, OT, and EA, respectively, whereas negative binomial-based algorithms had average values of 97.8%, 17.8%, 60%, and 55% for RTP, RFP, OT, and EA, respectively. Moreover, the EA was also affected by the region's population size

Epidemiological bridging by injection drug use drives an early HIV epidemic

Directory of Open Access Journals (Sweden)

Erik Volz

2010-09-01

Full Text Available The risk of acquiring sexually transmitted infections (STIs depends on individual behavior and the network of risky partnerships in which an individual participates. STI epidemics often spread rapidly and primarily among individuals central to transmission networks; and thus they often defy the mass-action principle since incidence is not proportional to the infectious fraction of the population. Here, we estimate the contact network structure for an Atlanta, Georgia community with heterogeneous sexual and drug-related risk behaviors and build a detailed transmission model for HIV through this population. We show that accurate estimation of epidemic incidence requires careful measurement and inclusion of diverse factors including concurrency (having multiple partners, the duration of partnerships, serosorting (preference for partners with matching disease state, and heterogeneity in the number and kinds of partners. In the focal population, we find that injection drug users (IDUs do not directly cause many secondary infections; yet they bridge the heterosexual and men-who-have-sex-with-men (MSM populations and are thereby indirectly responsible for extensive transmission. Keywords: HIV, Networks, Serosorting, Concurrency

Is thermogenesis a significant causal factor in preventing the "globesity" epidemic?

Science.gov (United States)

Hansen, Jens Carl; Gilman, Andrew P; Odland, Jon Øyvind

2010-08-01

During the last four decades the world has experienced an epidemic of overweight individuals in affluent as well as developing countries. The WHO has predicted a "globesity epidemic" with more than 1 billion adults being overweight and at least 300 million of these being clinically obese. Obesity among children and adolescents is of great significance. From a global population perspective, this epidemic in weight gain and its sequelae are the largest public health problems identified to date and have very significant adverse implications for population health, and have by now almost reached the proportion of a pandemic. While genetic changes have been discussed as a cause of the epidemic, there has been too little time since its start to enable enough genetic adaptation to take place for this to provide a valid explanation. Traditionally positive energy balance and sedentary life style have been regarded as the primary causal factors; however, these factors have so far failed to provide explanations for the entire problem. For these reasons it seems warranted to investigate other possible co-factors contributing to the "globesity epidemic" and to find efficient strategies to counteract further increases in the size and nature of the epidemic. The purpose of this paper is to discuss a potential preventive co-factor, thermogenesis. Special attention has been paid to the influence of ambient temperature as a grossly neglected factor in the debate. As most people today live and work at ambient temperatures close to their body temperature (the thermal neutral point), we hypothesise that this is an important causal co-factor in the "globesity" epidemic. The hypothesis: The null hypothesis that adaptive thermogenesis in brown adipose tissue in adult humans is not significant for weight loss is rejected. We propose the hypothesis that homoeothermic living conditions close to the thermogenic neutral level is an important causal co-factor in the "Globesity" Epidemic

Outbreak or Epidemic? How Obama's Language Choice Transformed the Ebola Outbreak Into an Epidemic.

Science.gov (United States)

Gesser-Edelsburg, Anat; Shir-Raz, Yaffa; Bar-Lev, Oshrat Sassoni; James, James J; Green, Manfred S

2016-08-01

Our aim was to examine in what terms leading newspapers' online sites described the current Ebola crisis. We employed a quantitative content analysis of terms attributed to Ebola. We found and analyzed 582 articles published between March 23 and September 30, 2014, on the online websites of 3 newspapers: The New York Times, Daily Mail, and Ynet. Our theoretical framework drew from the fields of health communication and emerging infectious disease communication, including such concepts as framing media literacy, risk signatures, and mental models. We found that outbreak and epidemic were used interchangeably in the articles. From September 16, 2014, onward, epidemic predominated, corresponding to when President Barack Obama explicitly referred to Ebola as an epidemic. Prior to Obama's speech, 86.8% of the articles (323) used the term outbreak and only 8.6% (32) used the term epidemic. Subsequently, both terms were used almost the same amount: 53.8% of the articles (113) used the term outbreak and 53.3% (112) used the term epidemic. Effective communication is crucial during public health emergencies such as Ebola, because language framing affects the decision-making process of social judgments and actions. The choice of one term (outbreak) over another (epidemic) can create different conceptualizations of the disease, thereby influencing the risk signature. (Disaster Med Public Health Preparedness. 2016;10:669-673).

Women with HIV in Indonesia: are they bridging a concentrated epidemic to the wider community?

Science.gov (United States)

Rahmalia, Annisa; Wisaksana, Rudi; Meijerink, Hinta; Indrati, Agnes R; Alisjahbana, Bachti; Roeleveld, Nel; van der Ven, Andre J A M; Laga, Marie; van Crevel, Reinout

2015-12-09

Male injecting drug users drove the onset of the HIV epidemic in Indonesia but over time more women have been diagnosed. We examined the relative proportion of female patients in an HIV cohort and characterized their probable transmission route and reproductive profile. Prospective cohort study in a referral hospital in West Java. Interviews with standardized questionnaires, physical and laboratory examinations were done for 2622 individuals enrolled in HIV care between 2007 and 2012. The proportion of women in this cohort was compared with national estimates. The general characteristics of HIV-infected women and men as well as the sexual and reproductive health of HIV-infected women were described. The proportion of female patients enrolled in HIV care increased from 22.2 % in 2007 to 38.3 % in 2012, in line with national estimates. Women were younger than men, fewer reported a history of IDU (16.1 vs. 73.8 %, p women were in their reproductive age, had children, and were not using contraceptives at the time of enrolment. HIV-infected women in Indonesia have specific characteristics that differ them from women in the general population. Further research to elucidate the characteristics of women exposed to HIV, their access to testing and care and sexual and reproductive needs can help reduce transmission to women and children in the context of concentrated HIV epidemic in Indonesia.

Stochastic inequalities and applications to dynamics analysis of a novel SIVS epidemic model with jumps

Directory of Open Access Journals (Sweden)

Xiaona Leng

2017-06-01

Full Text Available Abstract This paper proposes a new nonlinear stochastic SIVS epidemic model with double epidemic hypothesis and Lévy jumps. The main purpose of this paper is to investigate the threshold dynamics of the stochastic SIVS epidemic model. By using the technique of a series of stochastic inequalities, we obtain sufficient conditions for the persistence in mean and extinction of the stochastic system and the threshold which governs the extinction and the spread of the epidemic diseases. Finally, this paper describes the results of numerical simulations investigating the dynamical effects of stochastic disturbance. Our results significantly improve and generalize the corresponding results in recent literatures. The developed theoretical methods and stochastic inequalities technique can be used to investigate the high-dimensional nonlinear stochastic differential systems.

A laminar flow model of aerosol survival of epidemic and non-epidemic strains of Pseudomonas aeruginosa isolated from people with cystic fibrosis

Directory of Open Access Journals (Sweden)

Denton Miles

2008-06-01

Full Text Available Abstract Background Cystic fibrosis (CF is an inherited multi-system disorder characterised by chronic airway infection with pathogens such as Pseudomonas aeruginosa. Acquisition of P. aeruginosa by patients with CF is usually from the environment, but recent studies have demonstrated patient to patient transmission of certain epidemic strains, possibly via an airborne route. This study was designed to examine the survival of P. aeruginosa within artificially generated aerosols. Results Survival was effected by the solution used for aerosol generation. Within the aerosols it was adversely affected by an increase in air temperature. Both epidemic and non-epidemic strains of P. aeruginosa were able to survive within the aerosols, but strains expressing a mucoid phenotype had a survival advantage. Conclusion This would suggest that segregating individuals free of P. aeruginosa from those with chronic P. aeruginosa infection who are more likely to be infected with mucoid strains may help reduce the risk of cross-infection. Environmental factors also appear to influence bacterial survival. Warming and drying the air within clinical areas and avoidance of humidification devices may also be beneficial in reducing the risk of cross-infection.

Statistics of Epidemics in Networks by Passing Messages

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Shrestha, Munik Kumar

Epidemic processes are common out-of-equilibrium phenomena of broad interdisciplinary interest. In this thesis, we show how message-passing approach can be a helpful tool for simulating epidemic models in disordered medium like networks, and in particular for estimating the probability that a given node will become infectious at a particular time. The sort of dynamics we consider are stochastic, where randomness can arise from the stochastic events or from the randomness of network structures. As in belief propagation, variables or messages in message-passing approach are defined on the directed edges of a network. However, unlike belief propagation, where the posterior distributions are updated according to Bayes' rule, in message-passing approach we write differential equations for the messages over time. It takes correlations between neighboring nodes into account while preventing causal signals from backtracking to their immediate source, and thus avoids "echo chamber effects" where a pair of adjacent nodes each amplify the probability that the other is infectious. In our first results, we develop a message-passing approach to threshold models of behavior popular in sociology. These are models, first proposed by Granovetter, where individuals have to hear about a trend or behavior from some number of neighbors before adopting it themselves. In thermodynamic limit of large random networks, we provide an exact analytic scheme while calculating the time dependence of the probabilities and thus learning about the whole dynamics of bootstrap percolation, which is a simple model known in statistical physics for exhibiting discontinuous phase transition. As an application, we apply a similar model to financial networks, studying when bankruptcies spread due to the sudden devaluation of shared assets in overlapping portfolios. We predict that although diversification may be good for individual institutions, it can create dangerous systemic effects, and as a result

Evidence from epidemic appraisals in Nigeria

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Idoteyin O. Ezirim

2015-10-01

Full Text Available Although HIV prevalence has increased in most-at-risk populations (MARPs across Nigeria, effective programming was difficult because Nigeria lacked information for prevention programmes to target interventions that maximise coverage and cost effectiveness. Epidemic appraisals (EA were conducted in eight states to provide evidence for the planning, implementation and co-ordination of prevention interventions. Component 1: Mapping determined the size, typology and locations of MARPs. Component 2: Venue profiling identified and profiled venues where general populations engaged in high-risk behaviours. Component 3: Rural appraisals provided insights into risk behaviours and sexual networking in villages. States used mapping results to prioritise areas with a MARP coverage of 70% – 80% and then scale up interventions for non-brothel-based female sex workers (FSWs instead of focusing on brothel-based FSWs. The eight states prioritisedf unding for the high-coverage areas to ensure a minimum coverage level of 70% – 80% of MARPs was reached. The refocused resources led to cost efficiencies. Applying venue profiling results, six states implemented interventions at bars and night clubs – previously not covered. States also maximised intervention coverage for high-risk general populations; this led to the use of resources for general population interventions in a focused way rather than across an entire state. States focused on condom programmes in rural areas. EA results provided the evidence for focusing interventions for high MARP coverage as well as forhigh-risk general populations. The states applied the results and rapidly refocused their interventions, increasing the likelihood of having an impact on HIV transmission in those states. Nigeria is now implementing EAs in the remaining 29 states to effect national-level impact.

Epidemic spreading and global stability of an SIS model with an infective vector on complex networks

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Kang, Huiyan; Fu, Xinchu

2015-10-01

In this paper, we present a new SIS model with delay on scale-free networks. The model is suitable to describe some epidemics which are not only transmitted by a vector but also spread between individuals by direct contacts. In view of the biological relevance and real spreading process, we introduce a delay to denote average incubation period of disease in a vector. By mathematical analysis, we obtain the epidemic threshold and prove the global stability of equilibria. The simulation shows the delay will effect the epidemic spreading. Finally, we investigate and compare two major immunization strategies, uniform immunization and targeted immunization.

Dynamics and optimal control of a non-linear epidemic model with relapse and cure

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Lahrouz, A.; El Mahjour, H.; Settati, A.; Bernoussi, A.

2018-04-01

In this work, we introduce the basic reproduction number R0 for a general epidemic model with graded cure, relapse and nonlinear incidence rate in a non-constant population size. We established that the disease free-equilibrium state Ef is globally asymptotically exponentially stable if R0 1, we proved that the system model has at least one endemic state Ee. Then, by means of an appropriate Lyapunov function, we showed that Ee is unique and globally asymptotically stable under some acceptable biological conditions. On the other hand, we use two types of control to reduce the number of infectious individuals. The optimality system is formulated and solved numerically using a Gauss-Seidel-like implicit finite-difference method.

Temporal percolation of the susceptible network in an epidemic spreading.

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Valdez, Lucas Daniel; Macri, Pablo Alejandro; Braunstein, Lidia Adriana

2012-01-01

In this work, we study the evolution of the susceptible individuals during the spread of an epidemic modeled by the susceptible-infected-recovered (SIR) process spreading on the top of complex networks. Using an edge-based compartmental approach and percolation tools, we find that a time-dependent quantity ΦS(t), namely, the probability that a given neighbor of a node is susceptible at time t, is the control parameter of a node void percolation process involving those nodes on the network not-reached by the disease. We show that there exists a critical time t(c) above which the giant susceptible component is destroyed. As a consequence, in order to preserve a macroscopic connected fraction of the network composed by healthy individuals which guarantee its functionality, any mitigation strategy should be implemented before this critical time t(c). Our theoretical results are confirmed by extensive simulations of the SIR process.

What do young adults know about the HIV/AIDS epidemic? Findings from a population based study in Karachi, Pakistan

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Johansson Eva

2009-03-01

Full Text Available Abstract Background HIVAIDS is spreading globally, hitting the younger generations. In Pakistan, the prevalence of HIV in high-risk subpopulations is five per cent or higher. This poses a serious threat of a generalised epidemic especially among the younger population. In the wake of HIVAIDS epidemic this is worrying as a well informed younger generation is crucial in restricting the spread of this epidemic. This study investigated Pakistani young adults' (male and female knowledge and awareness of the HIV/AIDS disease. Methods A population-based, cross-sectional study of 1,650 male and female adults aged 17–21 years living in Karachi was conducted using a structured questionnaire. A multi-stage cluster sampling design was used to collect data representative of the general population in an urban area. Bivariate and multivariate analyses were performed separately for males and females. Results Of 1,650 subjects, 24 per cent (n = 390 reported that they had not heard of HIV/AIDS. Among the males, those with a poor knowledge were younger (AOR = 2.20; 95 per cent CI, 1.38, 3.49, with less than six years of schooling (AOR = 2.46; 1.29 4.68 and no computer at home (AOR = 1.88; 1.06 3.34. Among the females, the risk factors for poor knowledge were young age (AOR = 1.74; 1.22, 2.50, low socio-economic status (AOR = 1.54; 1.06, 2.22, lack of enrolment at school/college (AOR = 1.61; 1.09, 2.39 and being unmarried (AOR = 1.85; 1.05, 3.26. Conclusion Alarming gaps in knowledge relating to HIV/AIDS were detected. The study emphasises the need to educate young adults and equip them with the appropriate information and skills to enable them to protect themselves from HIV/AIDS. However, taboos surrounding public discussions of sexuality remain a key constraint to preventive activities.

Research Spotlight: Model suggests path to ending the ongoing Haitian cholera epidemic

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Schultz, Colin

2011-05-01

Since early November 2010 a deadly cholera epidemic has been spreading across the Caribbean nation of Haiti, killing thousands of people and infecting hundreds of thousands. While infection rates are being actively monitored, health organizations have been left without a clear understanding of exactly how the disease has spread across Haiti. Cholera can spread through exposure to contaminated water, and the disease travels over long distances if an infected individual moves around the country. Using representations of these two predominant dispersion mechanisms, along with information on the size of the susceptible population, the number of infected individuals, and the aquatic concentration of the cholera-causing bacteria for more than 500 communities, Bertuzzo et al. designed a model that was able to accurately reproduce the progression of the Haitian cholera epidemic. (Geophysical Research Letters, doi:10.1029/2011GL046823, 2011)

Structure and sensitivity analysis of individual-based predator–prey models

International Nuclear Information System (INIS)

Imron, Muhammad Ali; Gergs, Andre; Berger, Uta

2012-01-01

The expensive computational cost of sensitivity analyses has hampered the use of these techniques for analysing individual-based models in ecology. A relatively cheap computational cost, referred to as the Morris method, was chosen to assess the relative effects of all parameters on the model’s outputs and to gain insights into predator–prey systems. Structure and results of the sensitivity analysis of the Sumatran tiger model – the Panthera Population Persistence (PPP) and the Notonecta foraging model (NFM) – were compared. Both models are based on a general predation cycle and designed to understand the mechanisms behind the predator–prey interaction being considered. However, the models differ significantly in their complexity and the details of the processes involved. In the sensitivity analysis, parameters that directly contribute to the number of prey items killed were found to be most influential. These were the growth rate of prey and the hunting radius of tigers in the PPP model as well as attack rate parameters and encounter distance of backswimmers in the NFM model. Analysis of distances in both of the models revealed further similarities in the sensitivity of the two individual-based models. The findings highlight the applicability and importance of sensitivity analyses in general, and screening design methods in particular, during early development of ecological individual-based models. Comparison of model structures and sensitivity analyses provides a first step for the derivation of general rules in the design of predator–prey models for both practical conservation and conceptual understanding. - Highlights: ► Structure of predation processes is similar in tiger and backswimmer model. ► The two individual-based models (IBM) differ in space formulations. ► In both models foraging distance is among the sensitive parameters. ► Morris method is applicable for the sensitivity analysis even of complex IBMs.

Impact of human mobility on the emergence of dengue epidemics in Pakistan

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Wesolowski, Amy; Qureshi, Taimur; Boni, Maciej F.; Sundsøy, Pål Roe; Johansson, Michael A.; Rasheed, Syed Basit; Engø-Monsen, Kenth; Buckee, Caroline O.

2015-01-01

The recent emergence of dengue viruses into new susceptible human populations throughout Asia and the Middle East, driven in part by human travel on both local and global scales, represents a significant global health risk, particularly in areas with changing climatic suitability for the mosquito vector. In Pakistan, dengue has been endemic for decades in the southern port city of Karachi, but large epidemics in the northeast have emerged only since 2011. Pakistan is therefore representative of many countries on the verge of countrywide endemic dengue transmission, where prevention, surveillance, and preparedness are key priorities in previously dengue-free regions. We analyze spatially explicit dengue case data from a large outbreak in Pakistan in 2013 and compare the dynamics of the epidemic to an epidemiological model of dengue virus transmission based on climate and mobility data from ∼40 million mobile phone subscribers. We find that mobile phone-based mobility estimates predict the geographic spread and timing of epidemics in both recently epidemic and emerging locations. We combine transmission suitability maps with estimates of seasonal dengue virus importation to generate fine-scale dynamic risk maps with direct application to dengue containment and epidemic preparedness. PMID:26351662

Mathematical modeling, analysis and Markov Chain Monte Carlo simulation of Ebola epidemics

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Tulu, Thomas Wetere; Tian, Boping; Wu, Zunyou

Ebola virus infection is a severe infectious disease with the highest case fatality rate which become the global public health treat now. What makes the disease the worst of all is no specific effective treatment available, its dynamics is not much researched and understood. In this article a new mathematical model incorporating both vaccination and quarantine to study the dynamics of Ebola epidemic has been developed and comprehensively analyzed. The existence as well as uniqueness of the solution to the model is also verified and the basic reproduction number is calculated. Besides, stability conditions are also checked and finally simulation is done using both Euler method and one of the top ten most influential algorithm known as Markov Chain Monte Carlo (MCMC) method. Different rates of vaccination to predict the effect of vaccination on the infected individual over time and that of quarantine are discussed. The results show that quarantine and vaccination are very effective ways to control Ebola epidemic. From our study it was also seen that there is less possibility of an individual for getting Ebola virus for the second time if they survived his/her first infection. Last but not least real data has been fitted to the model, showing that it can used to predict the dynamic of Ebola epidemic.

A social contagious model of the obesity epidemic

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Huang, He; Yan, Zhijun; Chen, Yahong; Liu, Fangyan

2016-11-01

Obesity has been recognized as a global epidemic by WHO, followed by many empirical evidences to prove its infectiousness. However, the inter-person spreading dynamics of obesity are seldom studied. A distinguishing feature of the obesity epidemic is that it is driven by a social contagion process which cannot be perfectly described by the infectious disease models. In this paper, we propose a novel belief decision model based on the famous Dempster-Shafer theory of evidence to model obesity epidemic as the competing spread of two obesity-related behaviors: physical inactivity and physical activity. The transition of health states is described by an SIS model. Results reveal the existence of obesity epidemic threshold, above which obesity is quickly eradicated. When increasing the fading level of information spread, enlarging the clustering of initial obese seeds, or introducing small-world characteristics into the network topology, the threshold is easily met. Social discrimination against the obese people plays completely different roles in two cases: on one hand, when obesity cannot be eradicated, social discrimination can reduce the number of obese people; on the other hand, when obesity is eradicable, social discrimination may instead cause it breaking out.

New insights into the correlation structure of DSM-IV depression symptoms in the general population v. subsamples of depressed individuals.

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Foster, S; Mohler-Kuo, M

2018-06-01

Previous research failed to uncover a replicable dimensional structure underlying the symptoms of depression. We aimed to examine two neglected methodological issues in this research: (a) adjusting symptom correlations for overall depression severity; and (b) analysing general population samples v. subsamples of currently depressed individuals. Using population-based cross-sectional and longitudinal data from two nations (Switzerland, 5883 young men; USA, 2174 young men and 2244 young women) we assessed the dimensions of the nine DSM-IV depression symptoms in young adults. In each general-population sample and each subsample of currently depressed participants, we conducted a standardised process of three analytical steps, based on exploratory and confirmatory factor and bifactor analysis, to reveal any replicable dimensional structure underlying symptom correlations while controlling for overall depression severity. We found no evidence of a replicable dimensional structure across samples when adjusting symptom correlations for overall depression severity. In the general-population samples, symptoms correlated strongly and a single dimension of depression severity was revealed. Among depressed participants, symptom correlations were surprisingly weak and no replicable dimensions were identified, regardless of severity-adjustment. First, caution is warranted when considering studies assessing dimensions of depression because general population-based studies and studies of depressed individuals generate different data that can lead to different conclusions. This problem likely generalises to other models based on the symptoms' inter-relationships such as network models. Second, whereas the overall severity aligns individuals on a continuum of disorder intensity that allows non-affected individuals to be distinguished from affected individuals, the clinical evaluation and treatment of depressed individuals should focus directly on each individual's symptom profile.

Viral epidemics in a cell culture: novel high resolution data and their interpretation by a percolation theory based model.

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Gönci, Balázs; Németh, Valéria; Balogh, Emeric; Szabó, Bálint; Dénes, Ádám; Környei, Zsuzsanna; Vicsek, Tamás

2010-12-20

Because of its relevance to everyday life, the spreading of viral infections has been of central interest in a variety of scientific communities involved in fighting, preventing and theoretically interpreting epidemic processes. Recent large scale observations have resulted in major discoveries concerning the overall features of the spreading process in systems with highly mobile susceptible units, but virtually no data are available about observations of infection spreading for a very large number of immobile units. Here we present the first detailed quantitative documentation of percolation-type viral epidemics in a highly reproducible in vitro system consisting of tens of thousands of virtually motionless cells. We use a confluent astroglial monolayer in a Petri dish and induce productive infection in a limited number of cells with a genetically modified herpesvirus strain. This approach allows extreme high resolution tracking of the spatio-temporal development of the epidemic. We show that a simple model is capable of reproducing the basic features of our observations, i.e., the observed behaviour is likely to be applicable to many different kinds of systems. Statistical physics inspired approaches to our data, such as fractal dimension of the infected clusters as well as their size distribution, seem to fit into a percolation theory based interpretation. We suggest that our observations may be used to model epidemics in more complex systems, which are difficult to study in isolation.

Sudden transitions in coupled opinion and epidemic dynamics with vaccination

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Pires, Marcelo A.; Oestereich, André L.; Crokidakis, Nuno

2018-05-01

This work consists of an epidemic model with vaccination coupled with an opinion dynamics. Our objective was to study how disease risk perception can influence opinions about vaccination and therefore the spreading of the disease. Differently from previous works we have considered continuous opinions. The epidemic spreading is governed by an SIS-like model with an extra vaccinated state. In our model individuals vaccinate with a probability proportional to their opinions. The opinions change due to peer influence in pairwise interactions. The epidemic feedback to the opinion dynamics acts as an external field increasing the vaccination probability. We performed Monte Carlo simulations in fully-connected populations. Interestingly we observed the emergence of a first-order phase transition, besides the usual active-absorbing phase transition presented in the SIS model. Our simulations also show that with a certain combination of parameters, an increment in the initial fraction of the population that is pro-vaccine has a twofold effect: it can lead to smaller epidemic outbreaks in the short term, but it also contributes to the survival of the chain of infections in the long term. Our results also suggest that it is possible that more effective vaccines can decrease the long-term vaccine coverage. This is a counterintuitive outcome, but it is in line with empirical observations that vaccines can become a victim of their own success.

Time Prediction Models for Echinococcosis Based on Gray System Theory and Epidemic Dynamics.

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Zhang, Liping; Wang, Li; Zheng, Yanling; Wang, Kai; Zhang, Xueliang; Zheng, Yujian

2017-03-04

Echinococcosis, which can seriously harm human health and animal husbandry production, has become an endemic in the Xinjiang Uygur Autonomous Region of China. In order to explore an effective human Echinococcosis forecasting model in Xinjiang, three grey models, namely, the traditional grey GM(1,1) model, the Grey-Periodic Extensional Combinatorial Model (PECGM(1,1)), and the Modified Grey Model using Fourier Series (FGM(1,1)), in addition to a multiplicative seasonal ARIMA(1,0,1)(1,1,0)₄ model, are applied in this study for short-term predictions. The accuracy of the different grey models is also investigated. The simulation results show that the FGM(1,1) model has a higher performance ability, not only for model fitting, but also for forecasting. Furthermore, considering the stability and the modeling precision in the long run, a dynamic epidemic prediction model based on the transmission mechanism of Echinococcosis is also established for long-term predictions. Results demonstrate that the dynamic epidemic prediction model is capable of identifying the future tendency. The number of human Echinococcosis cases will increase steadily over the next 25 years, reaching a peak of about 1250 cases, before eventually witnessing a slow decline, until it finally ends.

Time Prediction Models for Echinococcosis Based on Gray System Theory and Epidemic Dynamics

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Liping Zhang

2017-03-01

Full Text Available Echinococcosis, which can seriously harm human health and animal husbandry production, has become an endemic in the Xinjiang Uygur Autonomous Region of China. In order to explore an effective human Echinococcosis forecasting model in Xinjiang, three grey models, namely, the traditional grey GM(1,1 model, the Grey-Periodic Extensional Combinatorial Model (PECGM(1,1, and the Modified Grey Model using Fourier Series (FGM(1,1, in addition to a multiplicative seasonal ARIMA(1,0,1(1,1,04 model, are applied in this study for short-term predictions. The accuracy of the different grey models is also investigated. The simulation results show that the FGM(1,1 model has a higher performance ability, not only for model fitting, but also for forecasting. Furthermore, considering the stability and the modeling precision in the long run, a dynamic epidemic prediction model based on the transmission mechanism of Echinococcosis is also established for long-term predictions. Results demonstrate that the dynamic epidemic prediction model is capable of identifying the future tendency. The number of human Echinococcosis cases will increase steadily over the next 25 years, reaching a peak of about 1250 cases, before eventually witnessing a slow decline, until it finally ends.

Heterogeneous network epidemics: real-time growth, variance and extinction of infection.

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Ball, Frank; House, Thomas

2017-09-01

Recent years have seen a large amount of interest in epidemics on networks as a way of representing the complex structure of contacts capable of spreading infections through the modern human population. The configuration model is a popular choice in theoretical studies since it combines the ability to specify the distribution of the number of contacts (degree) with analytical tractability. Here we consider the early real-time behaviour of the Markovian SIR epidemic model on a configuration model network using a multitype branching process. We find closed-form analytic expressions for the mean and variance of the number of infectious individuals as a function of time and the degree of the initially infected individual(s), and write down a system of differential equations for the probability of extinction by time t that are numerically fast compared to Monte Carlo simulation. We show that these quantities are all sensitive to the degree distribution-in particular we confirm that the mean prevalence of infection depends on the first two moments of the degree distribution and the variance in prevalence depends on the first three moments of the degree distribution. In contrast to most existing analytic approaches, the accuracy of these results does not depend on having a large number of infectious individuals, meaning that in the large population limit they would be asymptotically exact even for one initial infectious individual.

Networked SIS Epidemics With Awareness

KAUST Repository

Paarporn, Keith; Eksin, Ceyhun; Weitz, Joshua S.; Shamma, Jeff S.

2017-01-01

We study a susceptible-infected-susceptible epidemic process over a static contact network where the nodes have partial information about the epidemic state. They react by limiting their interactions with their neighbors when they believe

Spatially explicit models, generalized reproduction numbers and the prediction of patterns of waterborne disease

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Rinaldo, A.; Gatto, M.; Mari, L.; Casagrandi, R.; Righetto, L.; Bertuzzo, E.; Rodriguez-Iturbe, I.

2012-12-01

Metacommunity and individual-based theoretical models are studied in the context of the spreading of infections of water-borne diseases along the ecological corridors defined by river basins and networks of human mobility. The overarching claim is that mathematical models can indeed provide predictive insight into the course of an ongoing epidemic, potentially aiding real-time emergency management in allocating health care resources and by anticipating the impact of alternative interventions. To support the claim, we examine the ex-post reliability of published predictions of the 2010-2011 Haiti cholera outbreak from four independent modeling studies that appeared almost simultaneously during the unfolding epidemic. For each modeled epidemic trajectory, it is assessed how well predictions reproduced the observed spatial and temporal features of the outbreak to date. The impact of different approaches is considered to the modeling of the spatial spread of V. cholera, the mechanics of cholera transmission and in accounting for the dynamics of susceptible and infected individuals within different local human communities. A generalized model for Haitian epidemic cholera and the related uncertainty is thus constructed and applied to the year-long dataset of reported cases now available. Specific emphasis will be dedicated to models of human mobility, a fundamental infection mechanism. Lessons learned and open issues are discussed and placed in perspective, supporting the conclusion that, despite differences in methods that can be tested through model-guided field validation, mathematical modeling of large-scale outbreaks emerges as an essential component of future cholera epidemic control. Although explicit spatial modeling is made routinely possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is

Survivability Strategies for Epidemic Failures in Heterogeneous Networks

DEFF Research Database (Denmark)

Katsikas, Dimitrios; Fagertun, Anna Manolova; Ruepp, Sarah Renée

2013-01-01

Nowadays, transport networks, carry extremely large amounts of network traffic, and are widely spread across multiple geographical locations. As a result, any possible connectivity failure could directly impact the service delivery of a vast amount of users. Therefore, the network should be able...... protection, path restoration) X[1]X. Hence, assuming sufficient resources, network resilience can be achieved when a single failure occur (e.g. fiber cut). However, when it comes to simultaneous failures such as cascading and epidemic failures, the available solutions are expensive X[2]X. For Generalized...... the network X[6]X[7]X. This paper evaluates the reliability of a GMPLS transport network under epidemic failure scenarios. Thus, the aim is to increase the fault tolerance of the GMPLS technology when simultaneous failures occur impacting a large number of network nodes across an optical transport network...

Historical Epidemics Cartography Generated by Spatial Analysis: Mapping the Heterogeneity of Three Medieval "Plagues" in Dijon

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Galanaud, Pierre; Galanaud, Anne; Giraudoux, Patrick

2015-01-01

Objectives This work was designed to adapt Geographical Information System-based spatial analysis to the study of historical epidemics. We mapped "plague" deaths during three epidemics of the early 15th century, analyzed spatial distributions by applying the Kulldorff's method, and determined their relationships with the distribution of socio-professional categories in the city of Dijon. Materials and Methods Our study was based on a database including 50 annual tax registers (established from 1376 to 1447) indicating deaths and survivors among the heads of households, their home location, tax level and profession. The households of the deceased and survivors during 6 years with excess mortality were individually located on a georeferenced medieval map, established by taking advantage of the preserved geography of the historical center of Dijon. We searched for clusters of heads of households characterized by shared tax levels (high-tax payers, the upper decile; low-tax payers, the half charged at the minimum level) or professional activities and for clusters of differential mortality. Results High-tax payers were preferentially in the northern intramural part, as well as most wealthy or specialized professionals, whereas low-tax payers were preferentially in the southern part. During two epidemics, in 1400–1401 and 1428, areas of higher mortality were found in the northern part whereas areas of lower mortality were in the southern one. A high concentration of housing and the proximity to food stocks were common features of the most affected areas, creating suitable conditions for rats to pullulate. A third epidemic, lasting from 1438 to 1440 had a different and evolving geography: cases were initially concentrated around the southern gate, at the confluence of three rivers, they were then diffuse, and ended with residual foci of deaths in the northern suburb. Conclusion Using a selected historical source, we designed an approach allowing spatial analysis of

Molecular phylodynamics of the heterosexual HIV epidemic in the United Kingdom.

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Gareth J Hughes

2009-09-01

Full Text Available The heterosexual risk group has become the largest HIV infected group in the United Kingdom during the last 10 years, but little is known of the network structure and dynamics of viral transmission in this group. The overwhelming majority of UK heterosexual infections are of non-B HIV subtypes, indicating viruses originating among immigrants from sub-Saharan Africa. The high rate of HIV evolution, combined with the availability of a very high density sample of viral sequences from routine clinical care has allowed the phylodynamics of the epidemic to be investigated for the first time. Sequences of the viral protease and partial reverse transcriptase coding regions from 11,071 patients infected with HIV of non-B subtypes were studied. Of these, 2774 were closely linked to at least one other sequence by nucleotide distance. Including the closest sequences from the global HIV database identified 296 individuals that were in UK-based groups of 3 or more individuals. There were a total of 8 UK-based clusters of 10 or more, comprising 143/2774 (5% individuals, much lower than the figure of 25% obtained earlier for men who have sex with men (MSM. Sample dates were incorporated into relaxed clock phylogenetic analyses to estimate the dates of internal nodes. From the resulting time-resolved phylogenies, the internode lengths, used as estimates of maximum transmission intervals, had a median of 27 months overall, over twice as long as obtained for MSM (14 months, with only 2% of transmissions occurring in the first 6 months after infection. This phylodynamic analysis of non-B subtype HIV sequences representing over 40% of the estimated UK HIV-infected heterosexual population has revealed heterosexual HIV transmission in the UK is clustered, but on average in smaller groups and is transmitted with slower dynamics than among MSM. More effective intervention to restrict the epidemic may therefore be feasible, given effective diagnosis programmes.

Epidemic dynamics on a risk-based evolving social network

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Antwi, Shadrack; Shaw, Leah

2013-03-01

Social network models have been used to study how behavior affects the dynamics of an infection in a population. Motivated by HIV, we consider how a trade-off between benefits and risks of sexual connections determine network structure and disease prevalence. We define a stochastic network model with formation and breaking of links as changes in sexual contacts. Each node has an intrinsic benefit its neighbors derive from connecting to it. Nodes' infection status is not apparent to others, but nodes with more connections (higher degree) are assumed more likely to be infected. The probability to form and break links is determined by a payoff computed from the benefit and degree-dependent risk. The disease is represented by a SI (susceptible-infected) model. We study network and epidemic evolution via Monte Carlo simulation and analytically predict the behavior with a heterogeneous mean field approach. The dependence of network connectivity and infection threshold on parameters is determined, and steady state degree distribution and epidemic levels are obtained. We also study a situation where system-wide infection levels alter perception of risk and cause nodes to adjust their behavior. This is a case of an adaptive network, where node status feeds back to change network geometry.

Health-Care Access during the Ebola Virus Epidemic in Liberia.

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McQuilkin, Patricia A; Udhayashankar, Kanagasabai; Niescierenko, Michelle; Maranda, Louise

2017-09-01

The Ebola virus disease (EVD) epidemic, which began in West Africa in December 2013, claimed more than 11,000 lives, with more than 4,800 of these deaths occurring in Liberia. The epidemic had an additional effect of paralyzing the health-care systems in affected countries, which led to even greater mortality and morbidity. Little is known about the impact that the epidemic had on the provision of basic health care. During the period from March to May 2015, we undertook a nationwide, community-based survey to learn more about health-care access during the EVD epidemic in Liberia. A cluster sampling strategy was used to administer a structured in-person survey to heads of households located within the catchment areas surrounding all 21 government hospitals in Liberia. A total of 543 heads of household from all 15 counties in Liberia participated in the study; more than half (67%) of urban respondents and 46% of rural respondents stated that it was very difficult or impossible to access health care during the epidemic. In urban areas, only 20-30% of patients seeking care during the epidemic received care, and in rural areas, only 70-80% of those seeking care were able to access it. Patients requiring prenatal and obstetric care and emergency services had the most difficulty accessing care. The results of this survey support the observation that basic health care was extremely difficult to access during the EVD epidemic in Liberia. Our results underscore the critical need to support essential health-care services during humanitarian crises to minimize preventable morbidity and mortality.

Inferring infection hazard in wildlife populations by linking data across individual and population scales

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Pepin, Kim M.; Kay, Shannon L.; Golas, Ben D.; Shriner, Susan A.; Gilbert, Amy T.; Miller, Ryan S.; Graham, Andrea L.; Riley, Steven; Cross, Paul C.; Samuel, Michael D.; Hooten, Mevin B.; Hoeting, Jennifer A.; Lloyd-Smith, James O.; Webb, Colleen T.; Buhnerkempe, Michael G.

2017-01-01

Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease.

A modified anthrax toxin-based enzyme-linked immunospot assay reveals robust T cell responses in symptomatic and asymptomatic Ebola virus exposed individuals.

Science.gov (United States)

Herrera, Bobby Brooke; Hamel, Donald J; Oshun, Philip; Akinsola, Rolake; Akanmu, Alani S; Chang, Charlotte A; Eromon, Philomena; Folarin, Onikepe; Adeyemi, Kayode T; Happi, Christian T; Lu, Yichen; Ogunsola, Folasade; Kanki, Phyllis J

2018-05-01

Ebola virus (EBOV) caused more than 11,000 deaths during the 2013-2016 epidemic in West Africa without approved vaccines or immunotherapeutics. Despite its high lethality in some individuals, EBOV infection can produce little to no symptoms in others. A better understanding of the immune responses in individuals who experienced minimally symptomatic and asymptomatic infection could aid the development of more effective vaccines and antivirals against EBOV and related filoviruses. Between August and November 2017, blood samples were collected from 19 study participants in Lagos, Nigeria, including 3 Ebola virus disease (EVD) survivors, 10 individuals with documented close contact with symptomatic EVD patients, and 6 control healthcare workers for a cross-sectional serosurvey and T cell analysis. The Lagos samples, as well as archived serum collected from healthy individuals living in surrounding areas of the 1976 Democratic Republic of Congo (DRC) epidemic, were tested for EBOV IgG using commercial enzyme-linked immunosorbent assays (ELISAs) and Western blots. We detected antibodies in 3 out of 3 Lagos survivors and identified 2 seropositive individuals not known to have ever been infected. Of the DRC samples tested, we detected antibodies in 9 out of 71 (12.7%). To characterize the T cell responses in the Lagos samples, we developed an anthrax toxin-based enzyme-linked immunospot (ELISPOT) assay. The seropositive asymptomatic individuals had T cell responses against EBOV nucleoprotein, matrix protein, and glycoprotein 1 that were stronger in magnitude compared to the survivors. Our data provide further evidence of EBOV exposure in individuals without EVD-like illness and, for the first time, demonstrate that these individuals have T cell responses that are stronger in magnitude compared to severe cases. These findings suggest that T cell immunity may protect against severe EVD, which has important implications for vaccine development.

Expanding HIV testing efforts in concentrated epidemic settings: a population-based survey from rural Vietnam.

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Anastasia Pharris

Full Text Available BACKGROUND: To improve HIV prevention and care programs, it is important to understand the uptake of HIV testing and to identify population segments in need of increased HIV testing. This is particularly crucial in countries with concentrated HIV epidemics, where HIV prevalence continues to rise in the general population. This study analyzes determinants of HIV testing in a rural Vietnamese population in order to identify potential access barriers and areas for promoting HIV testing services. METHODS: A population-based cross-sectional survey of 1874 randomly sampled adults was linked to pregnancy, migration and economic cohort data from a demographic surveillance site (DSS. Multivariate logistic regression analysis was used to determine which factors were associated with having tested for HIV. RESULTS: The age-adjusted prevalence of ever-testing for HIV was 7.6%; however 79% of those who reported feeling at-risk of contracting HIV had never tested. In multivariate analysis, younger age (aOR 1.85, 95% CI 1.14-3.01, higher economic status (aOR 3.4, 95% CI 2.21-5.22, and semi-urban residence (aOR 2.37, 95% CI 1.53-3.66 were associated with having been tested for HIV. HIV testing rates did not differ between women of reproductive age who had recently been pregnant and those who had not. CONCLUSIONS: We found low testing uptake (6% among pregnant women despite an existing prevention of mother-to-child HIV testing policy, and lower-than-expected testing among persons who felt that they were at-risk of HIV. Poverty and residence in a more geographically remote location were associated with less HIV testing. In addition to current HIV testing strategies focusing on high-risk groups, we recommend targeting HIV testing in concentrated HIV epidemic settings to focus on a scaled-up provision of antenatal testing. Additional recommendations include removing financial and geographic access barriers to client-initiated testing, and encouraging provider

Expanding HIV testing efforts in concentrated epidemic settings: a population-based survey from rural Vietnam.

Science.gov (United States)

Pharris, Anastasia; Nguyen, Thi Kim Chuc; Tishelman, Carol; Brugha, Ruairí; Nguyen, Phuong Hoa; Thorson, Anna

2011-01-11

To improve HIV prevention and care programs, it is important to understand the uptake of HIV testing and to identify population segments in need of increased HIV testing. This is particularly crucial in countries with concentrated HIV epidemics, where HIV prevalence continues to rise in the general population. This study analyzes determinants of HIV testing in a rural Vietnamese population in order to identify potential access barriers and areas for promoting HIV testing services. A population-based cross-sectional survey of 1874 randomly sampled adults was linked to pregnancy, migration and economic cohort data from a demographic surveillance site (DSS). Multivariate logistic regression analysis was used to determine which factors were associated with having tested for HIV. The age-adjusted prevalence of ever-testing for HIV was 7.6%; however 79% of those who reported feeling at-risk of contracting HIV had never tested. In multivariate analysis, younger age (aOR 1.85, 95% CI 1.14-3.01), higher economic status (aOR 3.4, 95% CI 2.21-5.22), and semi-urban residence (aOR 2.37, 95% CI 1.53-3.66) were associated with having been tested for HIV. HIV testing rates did not differ between women of reproductive age who had recently been pregnant and those who had not. We found low testing uptake (6%) among pregnant women despite an existing prevention of mother-to-child HIV testing policy, and lower-than-expected testing among persons who felt that they were at-risk of HIV. Poverty and residence in a more geographically remote location were associated with less HIV testing. In addition to current HIV testing strategies focusing on high-risk groups, we recommend targeting HIV testing in concentrated HIV epidemic settings to focus on a scaled-up provision of antenatal testing. Additional recommendations include removing financial and geographic access barriers to client-initiated testing, and encouraging provider-initiated testing of those who believe that they are at-risk of

Geospatial analysis of emergency department visits for targeting community-based responses to the opioid epidemic.

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Daniel A Dworkis

Full Text Available The opioid epidemic in the United States carries significant morbidity and mortality and requires a coordinated response among emergency providers, outpatient providers, public health departments, and communities. Anecdotally, providers across the spectrum of care at Massachusetts General Hospital (MGH in Boston, MA have noticed that Charlestown, a community in northeast Boston, has been particularly impacted by the opioid epidemic and needs both emergency and longer-term resources. We hypothesized that geospatial analysis of the home addresses of patients presenting to the MGH emergency department (ED with opioid-related emergencies might identify "hot spots" of opioid-related healthcare needs within Charlestown that could then be targeted for further investigation and resource deployment. Here, we present a geospatial analysis at the United States census tract level of the home addresses of all patients who presented to the MGH ED for opioid-related emergency visits between 7/1/2012 and 6/30/2015, including 191 visits from 100 addresses in Charlestown, MA. Among the six census tracts that comprise Charlestown, we find a 9.5-fold difference in opioid-related ED visits, with 45% of all opioid-related visits from Charlestown originating in tract 040401. The signal from this census tract remains strong after adjusting for population differences between census tracts, and while this tract is one of the higher utilizing census tracts in Charlestown of the MGH ED for all cause visits, it also has a 2.9-fold higher rate of opioid-related visits than the remainder of Charlestown. Identifying this hot spot of opioid-related emergency needs within Charlestown may help re-distribute existing resources efficiently, empower community and ED-based physicians to advocate for their patients, and serve as a catalyst for partnerships between MGH and local community groups. More broadly, this analysis demonstrates that EDs can use geospatial analysis to address

Changes of MCP-1, FKN, and related cytokines in the serum and cerebrospinal fluid in children with epidemic encephalitis B

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Qian Wang

2017-09-01

Full Text Available Objective: To explore the changes of MCP-1, FKN, and related cytokines in the serum and cerebrospinal fluid (CSF in children with epidemic encephalitis B. Methods: A total of 40 children with epidemic encephalitis B who were admitted in our hospital from June, 2014 to June, 2017 were included in the study and divided into the severe group (n=15 and general group (n=25 according to the severity group. Moreover, 20 children who were suffered from oblique inguinal hernia, perineal adhesion, and cryptorchidism were served as the control group. The serum and CSF specimens were collected 24 h after admission and during the recovery period in children with epidemic encephalitis B. The serum specimen was collected 24 h after admission in the control group, and CSF specimen was collected during the lumbar puncture. ELISA was used to detect CMP-1, FKN, IL-1β, IL-18, and TNF-α levels in the serum and CSF. CMP-1, FKN, IL-1β, IL-18, and TNF-α levels in children with epidemic encephalitis B on the day after admission and 2-3 weeks after admission and in the control group were compared. The changes of CMP-1, FKN, IL-1β, IL-18, and TNF-α in children with severe and general epidemic encephalitis B were observed. Results: CMP-1 and FKN levels in the serum and CSF in children with epidemic encephalitis B in the critical stage were significantly higher than those in the recovery stage and in the control group. The serum CMP-1 and FKN levels in children with epidemic encephalitis B during the recovery stage were not significantly different from those in the control group, while CMP-1 and FKN levels in CSF were significantly higher than those in the control group. CMP-1 and FKN levels in the serum and CSF in children with severe epidemic encephalitis B were significantly higher than those in the general group. IL-1β, TNF-α, and IL-18 levels in the serum and CSF in children with epidemic encephalitis B during the critical stage were significantly higher than

Understanding Spatio-Temporal Variability in the Reproduction Ratio of the Bluetongue (BTV-1 Epidemic in Southern Spain (Andalusia in 2007 Using Epidemic Trees.

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S Napp

Full Text Available Andalusia (Southern Spain is considered one of the main routes of introduction of bluetongue virus (BTV into Europe, evidenced by a devastating epidemic caused by BTV-1 in 2007. Understanding the pattern and the drivers of BTV-1 spread in Andalusia is critical for effective detection and control of future epidemics. A long-standing metric for quantifying the behaviour of infectious diseases is the case-reproduction ratio (Rt, defined as the average number of secondary cases arising from a single infected case at time t (for t>0. Here we apply a method using epidemic trees to estimate the between-herd case reproduction ratio directly from epidemic data allowing the spatial and temporal variability in transmission to be described. We then relate this variability to predictors describing the hosts, vectors and the environment to better understand why the epidemic spread more quickly in some regions or periods. The Rt value for the BTV-1 epidemic in Andalusia peaked in July at 4.6, at the start of the epidemic, then decreased to 2.2 by August, dropped below 1 by September (0.8, and by October it had decreased to 0.02. BTV spread was the consequence of both local transmission within established disease foci and BTV expansion to distant new areas (i.e. new foci, which resulted in a high variability in BTV transmission, not only among different areas, but particularly through time, which suggests that general control measures applied at broad spatial scales are unlikely to be effective. This high variability through time was probably due to the impact of temperature on BTV transmission, as evidenced by a reduction in the value of Rt by 0.0041 for every unit increase (day in the extrinsic incubation period (EIP, which is itself directly dependent on temperature. Moreover, within the range of values at which BTV-1 transmission occurred in Andalusia (20.6°C to 29.5°C there was a positive correlation between temperature and Rt values, although the

Complex agent networks explaining the HIV epidemic among homosexual men in Amsterdam

NARCIS (Netherlands)

Mei, S.; Sloot, P.M.A.; Quax, R.; Zhu, Y.; Wang, W.

2010-01-01

Simulating the spreading of the human immunodeficiency virus (HIV) epidemic requires a detailed description of the population network, especially for small populations in which individuals can be represented in detail and accuracy. In this paper, we introduce the concept of a complex agent network

Individual and organizational predictors of depression in general practitioners.

OpenAIRE

Firth-Cozens, J

1998-01-01

BACKGROUND: High levels of stress and depression are seen in both general practitioners (GPs) and hospital doctors, and this has implications for patient care. It is therefore important to discover the individual and organizational causes of elevated symptoms so they can be tackled. AIM: To discover the relative importance of individual characteristics measured 10 years earlier compared with current organizational stressors in predicting depression in GPs. METHOD: Longitudinal questionnaire s...

Epidemics on adaptive networks with geometric constraints

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Shaw, Leah; Schwartz, Ira

2008-03-01

When a population is faced with an epidemic outbreak, individuals may modify their social behavior to avoid exposure to the disease. Recent work has considered models in which the contact network is rewired dynamically so that susceptibles avoid contact with infectives. We consider extensions in which the rewiring is subject to constraints that preserve key properties of the social network structure. Constraining to a fixed degree distribution destroys previously observed bistable behavior. The most effective rewiring strategy is found to depend on the spreading rate.

Epidemic spreading on dual-structure networks with mobile agents

Science.gov (United States)

Yao, Yiyang; Zhou, Yinzuo

2017-02-01

The rapid development of modern society continually transforms the social structure which leads to an increasingly distinct dual structure of higher population density in urban areas and lower density in rural areas. Such structure may induce distinctive spreading behavior of epidemics which does not happen in a single type structure. In this paper, we study the epidemic spreading of mobile agents on dual structure networks based on SIRS model. First, beyond the well known epidemic threshold for generic epidemic model that when the infection rate is below the threshold a pertinent infectious disease will die out, we find the other epidemic threshold which appears when the infection rate of a disease is relatively high. This feature of two thresholds for the SIRS model may lead to the elimination of infectious disease when social network has either high population density or low population density. Interestingly, however, we find that when a high density area is connected to a low density may cause persistent spreading of the infectious disease, even though the same disease will die out when it spreads in each single area. This phenomenon indicates the critical role of the connection between the two areas which could radically change the behavior of spreading dynamics. Our findings, therefore, provide new understanding of epidemiology pertinent to the characteristic modern social structure and have potential to develop controlling strategies accordingly.

[Epidemic parotiditis, a reportable disease].

Science.gov (United States)

Boverhoff, J C; Baart, J A

2013-01-01

Three consecutive patients with an acute swelling of one of the cheeks, were diagnosed with epidemic parotiditis. The first phase of the diagnostic procedure for an acute cheek swelling is to eliminate the possibility of odontogenic causes. When odontogenic problems have been excluded, non-dentition-related causes may be considered. An acute, progressive swelling in the preauricular area can often be attributed to an inflammation of the parotid gland, but epidemic parotiditis should also be considered. Epidemic parotiditis, or mumps, is caused by the mumps virus. Contamination occurs aerogenically. In the Netherlands, mumps vaccine is an ingredient of the governmental combined mump-measles-rubella inoculation programme. However, in recent years several small-scale parotiditis epidemics have broken out, predominantly among young, inoculated adults. Oropharyngeal mucus and blood samples are needed to diagnose the disease. Each case of the disease should be reported to the community healthcare service.

Burst of virus infection and a possibly largest epidemic threshold of non-Markovian susceptible-infected-susceptible processes on networks

Science.gov (United States)

Liu, Qiang; Van Mieghem, Piet

2018-02-01

Since a real epidemic process is not necessarily Markovian, the epidemic threshold obtained under the Markovian assumption may be not realistic. To understand general non-Markovian epidemic processes on networks, we study the Weibullian susceptible-infected-susceptible (SIS) process in which the infection process is a renewal process with a Weibull time distribution. We find that, if the infection rate exceeds 1 /ln(λ1+1 ) , where λ1 is the largest eigenvalue of the network's adjacency matrix, then the infection will persist on the network under the mean-field approximation. Thus, 1 /ln(λ1+1 ) is possibly the largest epidemic threshold for a general non-Markovian SIS process with a Poisson curing process under the mean-field approximation. Furthermore, non-Markovian SIS processes may result in a multimodal prevalence. As a byproduct, we show that a limiting Weibullian SIS process has the potential to model bursts of a synchronized infection.

Viral epidemics in a cell culture: novel high resolution data and their interpretation by a percolation theory based model.

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Balázs Gönci

2010-12-01

Full Text Available Because of its relevance to everyday life, the spreading of viral infections has been of central interest in a variety of scientific communities involved in fighting, preventing and theoretically interpreting epidemic processes. Recent large scale observations have resulted in major discoveries concerning the overall features of the spreading process in systems with highly mobile susceptible units, but virtually no data are available about observations of infection spreading for a very large number of immobile units. Here we present the first detailed quantitative documentation of percolation-type viral epidemics in a highly reproducible in vitro system consisting of tens of thousands of virtually motionless cells. We use a confluent astroglial monolayer in a Petri dish and induce productive infection in a limited number of cells with a genetically modified herpesvirus strain. This approach allows extreme high resolution tracking of the spatio-temporal development of the epidemic. We show that a simple model is capable of reproducing the basic features of our observations, i.e., the observed behaviour is likely to be applicable to many different kinds of systems. Statistical physics inspired approaches to our data, such as fractal dimension of the infected clusters as well as their size distribution, seem to fit into a percolation theory based interpretation. We suggest that our observations may be used to model epidemics in more complex systems, which are difficult to study in isolation.

Concurrency can drive an HIV epidemic by moving R0 across the epidemic threshold

NARCIS (Netherlands)

Leung, Ka Yin; Kretzschmar, Mirjam

2015-01-01

OBJECTIVE: The objective of this study is to investigate whether concurrency can drive an HIV epidemic by moving R0 across the epidemic threshold. DESIGN AND METHODS: We use a mathematical framework for a dynamic partnership network and the spread of a one-stage infection to study how concurrency is

Influence of Media on Seasonal Influenza Epidemic Curves.

Science.gov (United States)

Saito, Satoshi; Saito, Norihiro; Itoga, Masamichi; Ozaki, Hiromi; Kimura, Toshiyuki; Okamura, Yuji; Murakami, Hiroshi; Kayaba, Hiroyuki

2016-09-01

Theoretical investigations predicting the epidemic curves of seasonal influenza have been demonstrated so far; however, there is little empirical research using ever accumulated epidemic curves. The effects of vaccine coverage and information distribution on influenza epidemics were evaluated. Four indices for epidemics (i.e., onset-peak duration, onset-end duration, ratio of the onset-peak duration to onset-end duration and steepness of epidemic curves) were defined, and the correlations between these indices and anti-flu drug prescription dose, vaccine coverage, the volume of media and search trend on influenza through internet were analyzed. Epidemiological data on seasonal influenza epidemics from 2002/2003 to 2013/2014 excluding 2009/2010 season were collected from National Institute of Infectious Diseases of Japan. The onset-peak duration and its ratio to onset-end duration correlated inversely with the volume of anti-flu drug prescription. Onset-peak duration correlated positively with media information volume on influenza. The steepness of the epidemic curve, and anti-flu drug prescription dose inversely correlated with the volume of media information. Pre-epidemic search trend and media volume on influenza correlated with the vaccine coverage in the season. Vaccine coverage had no strong effect on epidemic curve. Education through media has an effect on the epidemic curve of seasonal influenza. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Ebola epidemic--Liberia, March-October 2014.

Science.gov (United States)

Nyenswah, Tolbert; Fahnbulleh, Miatta; Massaquoi, Moses; Nagbe, Thomas; Bawo, Luke; Falla, James Dorbor; Kohar, Henry; Gasasira, Alex; Nabeth, Pierre; Yett, Sheldon; Gergonne, Bernadette; Casey, Sean; Espinosa, Benjamin; McCoy, Andrea; Feldman, Heinz; Hensley, Lisa; Baily, Mark; Fields, Barry; Lo, Terrence; Lindblade, Kim; Mott, Josh; Boulanger, Lucy; Christie, Athalia; Wang, Susan; Montgomery, Joel; Mahoney, Frank

2014-11-21

On March 21, 2014, the Guinea Ministry of Health reported the outbreak of an illness characterized by fever, severe diarrhea, vomiting and a high fatality rate (59%), leading to the first known epidemic of Ebola virus disease (Ebola) in West Africa and the largest and longest Ebola epidemic in history. As of November 2, Liberia had reported the largest number of cases (6,525) and deaths (2,697) among the three affected countries of West Africa with ongoing transmission (Guinea, Liberia, and Sierra Leone). The response strategy in Liberia has included management of the epidemic through an incident management system (IMS) in which the activities of all partners are coordinated. Within the IMS, key strategies for epidemic control include surveillance, case investigation, laboratory confirmation, contact tracing, safe transportation of persons with suspected Ebola, isolation, infection control within the health care system, community engagement, and safe burial. This report provides a brief overview of the progression of the epidemic in Liberia and summarizes the interventions implemented.

Optimal control of epidemic information dissemination over networks.

Science.gov (United States)

Chen, Pin-Yu; Cheng, Shin-Ming; Chen, Kwang-Cheng

2014-12-01

Information dissemination control is of crucial importance to facilitate reliable and efficient data delivery, especially in networks consisting of time-varying links or heterogeneous links. Since the abstraction of information dissemination much resembles the spread of epidemics, epidemic models are utilized to characterize the collective dynamics of information dissemination over networks. From a systematic point of view, we aim to explore the optimal control policy for information dissemination given that the control capability is a function of its distribution time, which is a more realistic model in many applications. The main contributions of this paper are to provide an analytically tractable model for information dissemination over networks, to solve the optimal control signal distribution time for minimizing the accumulated network cost via dynamic programming, and to establish a parametric plug-in model for information dissemination control. In particular, we evaluate its performance in mobile and generalized social networks as typical examples.

Epidemic spreading on weighted complex networks

International Nuclear Information System (INIS)

Sun, Ye; Liu, Chuang; Zhang, Chu-Xu; Zhang, Zi-Ke

2014-01-01

Nowadays, the emergence of online services provides various multi-relation information to support the comprehensive understanding of the epidemic spreading process. In this Letter, we consider the edge weights to represent such multi-role relations. In addition, we perform detailed analysis of two representative metrics, outbreak threshold and epidemic prevalence, on SIS and SIR models. Both theoretical and simulation results find good agreements with each other. Furthermore, experiments show that, on fully mixed networks, the weight distribution on edges would not affect the epidemic results once the average weight of whole network is fixed. This work may shed some light on the in-depth understanding of epidemic spreading on multi-relation and weighted networks.

Epidemic spreading on weighted complex networks

Energy Technology Data Exchange (ETDEWEB)

Sun, Ye [Institute of Information Economy, Hangzhou Normal University, Hangzhou 311121 (China); Alibaba Research Center of Complexity Science, Hangzhou Normal University, Hangzhou 311121 (China); Liu, Chuang, E-mail: liuchuang@hznu.edu.cn [Institute of Information Economy, Hangzhou Normal University, Hangzhou 311121 (China); Alibaba Research Center of Complexity Science, Hangzhou Normal University, Hangzhou 311121 (China); Zhang, Chu-Xu [Institute of Information Economy, Hangzhou Normal University, Hangzhou 311121 (China); Alibaba Research Center of Complexity Science, Hangzhou Normal University, Hangzhou 311121 (China); Zhang, Zi-Ke, E-mail: zhangzike@gmail.com [Institute of Information Economy, Hangzhou Normal University, Hangzhou 311121 (China); Alibaba Research Center of Complexity Science, Hangzhou Normal University, Hangzhou 311121 (China)

2014-01-31

Nowadays, the emergence of online services provides various multi-relation information to support the comprehensive understanding of the epidemic spreading process. In this Letter, we consider the edge weights to represent such multi-role relations. In addition, we perform detailed analysis of two representative metrics, outbreak threshold and epidemic prevalence, on SIS and SIR models. Both theoretical and simulation results find good agreements with each other. Furthermore, experiments show that, on fully mixed networks, the weight distribution on edges would not affect the epidemic results once the average weight of whole network is fixed. This work may shed some light on the in-depth understanding of epidemic spreading on multi-relation and weighted networks.

Hub nodes inhibit the outbreak of epidemic under voluntary vaccination

Energy Technology Data Exchange (ETDEWEB)

Zhang Haifeng; Wang Binghong [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China)], E-mail: bhwang@ustc.edu.cn; Zhang Jie; Small, Michael [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (China)], E-mail: ensmall@polyu.edu.hk; Zhou Changsong [Department of Physics, Centre for Nonlinear Studies, and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Hong Kong Baptist University, Kowloon Tong, Hong Kong (China)

2010-02-15

It is commonly believed that epidemic spreading on scale-free networks is difficult to control and that the disease can spread even with a low infection rate, lacking an epidemic threshold. In this paper, we study epidemic spreading on complex networks under the framework of game theory, in which a voluntary vaccination strategy is incorporated. In particular, individuals face the 'dilemma' of vaccination: they have to decide whether or not to vaccinate according to the trade-off between the risk and the side effects or cost of vaccination. Remarkably and quite excitingly, we find that disease outbreak can be more effectively inhibited on scale-free networks than on random networks. This is because the hub nodes of scale-free networks are more inclined to take self-vaccination after balancing the pros and cons. This result is encouraging as it indicates that real-world networks, which are often claimed to be scale free, can be favorably and easily controlled under voluntary vaccination. Our work provides a way of understanding how to prevent the outbreak of diseases under voluntary vaccination, and is expected to provide valuable information on effective disease control and appropriate decision-making.

Hub nodes inhibit the outbreak of epidemic under voluntary vaccination

International Nuclear Information System (INIS)

Zhang Haifeng; Wang Binghong; Zhang Jie; Small, Michael; Zhou Changsong

2010-01-01

It is commonly believed that epidemic spreading on scale-free networks is difficult to control and that the disease can spread even with a low infection rate, lacking an epidemic threshold. In this paper, we study epidemic spreading on complex networks under the framework of game theory, in which a voluntary vaccination strategy is incorporated. In particular, individuals face the 'dilemma' of vaccination: they have to decide whether or not to vaccinate according to the trade-off between the risk and the side effects or cost of vaccination. Remarkably and quite excitingly, we find that disease outbreak can be more effectively inhibited on scale-free networks than on random networks. This is because the hub nodes of scale-free networks are more inclined to take self-vaccination after balancing the pros and cons. This result is encouraging as it indicates that real-world networks, which are often claimed to be scale free, can be favorably and easily controlled under voluntary vaccination. Our work provides a way of understanding how to prevent the outbreak of diseases under voluntary vaccination, and is expected to provide valuable information on effective disease control and appropriate decision-making.

Epidemic spreading on dynamical networks with temporary hubs and stable scale-free degree distribution

International Nuclear Information System (INIS)

Wu, An-Cai

2014-01-01

Recent empirical analyses of some realistic dynamical networks have demonstrated that their degree distributions are stable scale-free (SF), but the instantaneous well-connected hubs at one point of time can quickly become weakly connected. Motivated by these empirical results, we propose a simple toy dynamical agent-to-agent contact network model, in which each agent stays at one node of a static underlay network and the nearest neighbors swap their positions with each other. Although the degree distribution of the dynamical network model at any one time is equal to that in the static underlay network, the numbers and identities of each agent’s contacts will change over time. It is found that the dynamic interaction tends to suppress epidemic spreading in terms of larger epidemic threshold, smaller prevalence (the fraction of infected individuals) and smaller velocity of epidemic outbreak. Furthermore, the dynamic interaction results in the prevalence to undergo a phase transition at a finite threshold of the epidemic spread rate in the thermodynamic limit, which is in contradiction to the absence of an epidemic threshold in static SF networks. Some of these findings obtained from heterogeneous mean-field theory are in good agreement with numerical simulations. (paper)

The development of a massive open online course during the 2014-15 Ebola virus disease epidemic.

Science.gov (United States)

Evans, Dabney P; Luffy, Samantha M; Parisi, Stephanie; Del Rio, Carlos

2017-09-01

Timely training was urgently needed at the onset of the 2014 Ebola virus disease epidemic. Massive open online courses (MOOCs) have grown in popularity, though little is known about their utility in time-sensitive situations, including infectious disease outbreaks. We created the first English language massive open online course on Ebola virus disease. Designed by a team representing various units of Emory University and six partner institutions, the six module course was aimed at a global general audience but also relevant for health care professionals. Over 7,000 learners from 170 countries participated in the initial course offering. More than a third of learners were from emerging economies, including seven percent from Africa, and another 13% from countries outside the United States who received individuals requiring treatment for Ebola virus disease. Creating and producing the first English language MOOC on EVD in a short time period required effective collaboration and strong coordination between subject matter and course development experts from Emory. Through these collaborative efforts, the development team was able to provide urgently needed training and educational materials while the epidemic of EVD continued to radiate through West Africa. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimal allocation of resources for suppressing epidemic spreading on networks

Science.gov (United States)

Chen, Hanshuang; Li, Guofeng; Zhang, Haifeng; Hou, Zhonghuai

2017-07-01

Efficient allocation of limited medical resources is crucial for controlling epidemic spreading on networks. Based on the susceptible-infected-susceptible model, we solve the optimization problem of how best to allocate the limited resources so as to minimize prevalence, providing that the curing rate of each node is positively correlated to its medical resource. By quenched mean-field theory and heterogeneous mean-field (HMF) theory, we prove that an epidemic outbreak will be suppressed to the greatest extent if the curing rate of each node is directly proportional to its degree, under which the effective infection rate λ has a maximal threshold λcopt=1 / , where is the average degree of the underlying network. For a weak infection region (λ ≳λcopt ), we combine perturbation theory with the Lagrange multiplier method (LMM) to derive the analytical expression of optimal allocation of the curing rates and the corresponding minimized prevalence. For a general infection region (λ >λcopt ), the high-dimensional optimization problem is converted into numerically solving low-dimensional nonlinear equations by the HMF theory and LMM. Counterintuitively, in the strong infection region the low-degree nodes should be allocated more medical resources than the high-degree nodes to minimize prevalence. Finally, we use simulated annealing to validate the theoretical results.

Epidemic cholera spreads like wildfire

Science.gov (United States)

Roy, Manojit; Zinck, Richard D.; Bouma, Menno J.; Pascual, Mercedes

2014-01-01

Cholera is on the rise globally, especially epidemic cholera which is characterized by intermittent and unpredictable outbreaks that punctuate periods of regional disease fade-out. These epidemic dynamics remain however poorly understood. Here we examine records for epidemic cholera over both contemporary and historical timelines, from Africa (1990-2006) and former British India (1882-1939). We find that the frequency distribution of outbreak size is fat-tailed, scaling approximately as a power-law. This pattern which shows strong parallels with wildfires is incompatible with existing cholera models developed for endemic regions, as it implies a fundamental role for stochastic transmission and local depletion of susceptible hosts. Application of a recently developed forest-fire model indicates that epidemic cholera dynamics are located above a critical phase transition and propagate in similar ways to aggressive wildfires. These findings have implications for the effectiveness of control measures and the mechanisms that ultimately limit the size of outbreaks.

Contact allergy epidemics and their controls

DEFF Research Database (Denmark)

Thyssen, Jacob Pontoppidan; Johansen, Jeanne Duus; Menné, Torkil

2007-01-01

Contact dermatitis can be severe and lead to sick leave as well as significant healthcare expenses. The aim of this review is to present the published knowledge on 6 historical epidemics of contact allergy to apply this knowledge on the prevention and control of future contact allergy epidemics. ...... to prevent contact allergy epidemics. It is essential that dermatologist, scientists, administrators, and consumers organize and structure known methods to accelerate the control of emerging contact allergens....

Epidemics scenarios in the "Romantic network".

Directory of Open Access Journals (Sweden)

Alexsandro M Carvalho

Full Text Available The networks of sexual contacts together with temporal interactions play key roles in the spread of sexually transmitted infections. Unfortunately, data for this kind of network is scarce. One of the few exceptions, the "Romantic network", is a complete structure of a real sexual network in a high school. Based on many network measurements the authors of the work have concluded that it does not correspond to any other model network. Regarding the temporal structure, several studies indicate that relationship timing can have an effect on the diffusion throughout networks, as relationship order determines transmission routes. The aim is to check if the particular structure, static and dynamic, of the Romantic network is determinant for the propagation of an STI. We performed simulations in two scenarios: the static network where all contacts are available and the dynamic case where contacts evolve over time. In the static case, we compared the epidemic results in the Romantic network with some paradigmatic topologies. In the dynamic scenario, we considered the dynamics of formation of pairs in the Romantic network and we studied the propagation of the diseases. Our results suggest that although this real network cannot be labeled as a Watts-Strogatz network, it is, in regard to the propagation of an STI, very similar to a high disorder network. Additionally, we found that: the effect that any individual contacting an externally infected subject is to make the network closer to a fully connected one, the higher the contact degree of patient zero the faster the spread of the outbreaks, and the epidemic impact is proportional to the numbers of contacts per unit time. Finally, our simulations confirm that relationship timing severely reduced the final outbreak size, and also, show a clear correlation between the average degree and the outbreak size over time.

Association of Drought with Typhus Epidemics in Central Mexico

Science.gov (United States)

Acuna-Soto, R.; Stahle, D.; Villanueva Diaz, J.; Therrell, M.

2007-05-01

Typhus is an acute infectious disease caused by the bacteria Rickettsia prowazekii, which is transmitted among humans by the body lice (Pediculus humanus corporis). The disease is highly contagious and transmission is favored in populations living in crowded conditions. Under these circumstances, typhus transmission is facilitated by factors that favor the colonization and proliferation of body lice such as absence of personal hygiene and wearing the same clothes for long periods of time. Historically, periods of war and famine were associated with devastating epidemics with high mortality rates in many parts of the world. Central Mexico has a long record of typhus epidemics. In this region, at > 2000 meters above sea level, the disease was endemic and occurred with a seasonal pattern in winter, with occasional large epidemics. Recently, we completed a chronology of epidemics in Mexico. A total of 22 well-defined major typhus epidemics were identified between 1650 and 1920. All of them caused periods of increased mortality that lasted 2 - 4 years (more than one standard deviation from the previous ten year period). The record of typhus epidemics was evaluated against the tree-ring record of Cuauhtmoc La Fragua, Puebla. This chronology, based on Douglas fir, has demonstrated to be a faithful record of precipitation in central Mexico. The results indicate that a statistically significant drought (t test, p first year of all 22 large outbreaks of typhus in recent Mexican history. No distinction is made between times of peace and war. This indicates that drought alone was capable of inducing the social conditions for increased transmission of typhus in pre-industrial central Mexico.

Quarantine-generated phase transition in epidemic spreading

Science.gov (United States)

Lagorio, C.; Dickison, M.; Vazquez, F.; Braunstein, L. A.; Macri, P. A.; Migueles, M. V.; Havlin, S.; Stanley, H. E.

2011-02-01

We study the critical effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible individuals protect themselves by disconnecting their links to infected neighbors with probability w and reconnecting them to other susceptible individuals chosen at random. Starting from a single infected individual, we show by an analytical approach and simulations that there is a phase transition at a critical rewiring (quarantine) threshold wc separating a phase (wspread out. We find that in our model the topology of the network strongly affects the size of the propagation and that wc increases with the mean degree and heterogeneity of the network. We also find that wc is reduced if we perform a preferential rewiring, in which the rewiring probability is proportional to the degree of infected nodes.

Defining and detecting malaria epidemics in south-east Iran.

Science.gov (United States)

McKelvie, William R; Haghdoost, Ali Akbar; Raeisi, Ahmad

2012-03-23

A lack of consensus on how to define malaria epidemics has impeded the evaluation of early detection systems. This study aimed to develop local definitions of malaria epidemics in a known malarious area of Iran, and to use that definition to evaluate the validity of several epidemic alert thresholds. Epidemic definition variables generated from surveillance data were plotted against weekly malaria counts to assess which most accurately labelled aberrations. Various alert thresholds were then generated from weekly counts or log counts. Finally, the best epidemic definition was used to calculate and compare sensitivities, specificities, detection delays, and areas under ROC curves of the alert thresholds. The best epidemic definition used a minimum duration of four weeks and week-specific and overall smoothed geometric means plus 1.0 standard deviation. It defined 13 epidemics. A modified C-SUM alert of untransformed weekly counts using a threshold of mean+0.25 SD had the highest combined sensitivity and specificity. Untransformed C-SUM alerts also had the highest area under the ROC curve. Defining local malaria epidemics using objective criteria facilitated the evaluation of alert thresholds. This approach needs further study to refine epidemic definitions and prospectively evaluate epidemic alerts.

Stability of the Associations between Early Life Risk Indicators and Adolescent Overweight over the Evolving Obesity Epidemic

DEFF Research Database (Denmark)

Graversen, Lise; Sørensen, Thorkild I A; Petersen, Liselotte

2014-01-01

BACKGROUND: Pre- and perinatal factors and preschool body size may help identify children developing overweight, but these factors might have changed during the development of the obesity epidemic. OBJECTIVE: We aimed to assess the associations between early life risk indicators and overweight...... at the age of 9 and 15 years at different stages of the obesity epidemic. METHODS: We used two population-based Northern Finland Birth Cohorts including 4111 children born in 1966 (NFBC1966) and 5414 children born in 1985-1986 (NFBC1986). In both cohorts, we used the same a priori defined prenatal factors......, maternal body mass index (BMI), birth weight, infant weight (age 5 months and 1 year), and preschool BMI (age 2-5 years). We used internal references in early childhood to define percentiles of body size (90) and generalized linear models to study the association with overweight...

Collective effect of personal behavior induced preventive measures and differential rate of transmission on spread of epidemics

Science.gov (United States)

Sagar, Vikram; Zhao, Yi

2017-02-01

In the present work, the effect of personal behavior induced preventive measures is studied on the spread of epidemics over scale free networks that are characterized by the differential rate of disease transmission. The role of personal behavior induced preventive measures is parameterized in terms of variable λ, which modulates the number of concurrent contacts a node makes with the fraction of its neighboring nodes. The dynamics of the disease is described by a non-linear Susceptible Infected Susceptible model based upon the discrete time Markov Chain method. The network mean field approach is generalized to account for the effect of non-linear coupling between the aforementioned factors on the collective dynamics of nodes. The upper bound estimates of the disease outbreak threshold obtained from the mean field theory are found to be in good agreement with the corresponding non-linear stochastic model. From the results of parametric study, it is shown that the epidemic size has inverse dependence on the preventive measures (λ). It has also been shown that the increase in the average degree of the nodes lowers the time of spread and enhances the size of epidemics.

Defining epidemics in computer simulation models: How do definitions influence conclusions?

Directory of Open Access Journals (Sweden)

Carolyn Orbann

2017-06-01

Full Text Available Computer models have proven to be useful tools in studying epidemic disease in human populations. Such models are being used by a broader base of researchers, and it has become more important to ensure that descriptions of model construction and data analyses are clear and communicate important features of model structure. Papers describing computer models of infectious disease often lack a clear description of how the data are aggregated and whether or not non-epidemic runs are excluded from analyses. Given that there is no concrete quantitative definition of what constitutes an epidemic within the public health literature, each modeler must decide on a strategy for identifying epidemics during simulation runs. Here, an SEIR model was used to test the effects of how varying the cutoff for considering a run an epidemic changes potential interpretations of simulation outcomes. Varying the cutoff from 0% to 15% of the model population ever infected with the illness generated significant differences in numbers of dead and timing variables. These results are important for those who use models to form public health policy, in which questions of timing or implementation of interventions might be answered using findings from computer simulation models.

The fastest spreader in SIS epidemics on networks

Science.gov (United States)

He, Zhidong; Van Mieghem, Piet

2018-05-01

Identifying the fastest spreaders in epidemics on a network helps to ensure an efficient spreading. By ranking the average spreading time for different spreaders, we show that the fastest spreader may change with the effective infection rate of a SIS epidemic process, which means that the time-dependent influence of a node is usually strongly coupled to the dynamic process and the underlying network. With increasing effective infection rate, we illustrate that the fastest spreader changes from the node with the largest degree to the node with the shortest flooding time. (The flooding time is the minimum time needed to reach all other nodes if the process is reduced to a flooding process.) Furthermore, by taking the local topology around the spreader and the average flooding time into account, we propose the spreading efficiency as a metric to quantify the efficiency of a spreader and identify the fastest spreader, which is adaptive to different infection rates in general networks.

Heightened vulnerability to MDR-TB epidemics after controlling drug-susceptible TB.

Directory of Open Access Journals (Sweden)

Jason D Bishai

2010-09-01

Full Text Available Prior infection with one strain TB has been linked with diminished likelihood of re-infection by a new strain. This paper attempts to determine the role of declining prevalence of drug-susceptible TB in enabling future epidemics of MDR-TB.A computer simulation of MDR-TB epidemics was developed using an agent-based model platform programmed in NetLogo (See http://mdr.tbtools.org/. Eighty-one scenarios were created, varying levels of treatment quality, diagnostic accuracy, microbial fitness cost, and the degree of immunogenicity elicited by drug-susceptible TB. Outcome measures were the number of independent MDR-TB cases per trial and the proportion of trials resulting in MDR-TB epidemics for a 500 year period after drug therapy for TB is introduced.MDR-TB epidemics propagated more extensively after TB prevalence had fallen. At a case detection rate of 75%, improving therapeutic compliance from 50% to 75% can reduce the probability of an epidemic from 45% to 15%. Paradoxically, improving the case-detection rate from 50% to 75% when compliance with DOT is constant at 75% increases the probability of MDR-TB epidemics from 3% to 45%.The ability of MDR-TB to spread depends on the prevalence of drug-susceptible TB. Immunologic protection conferred by exposure to drug-susceptible TB can be a crucial factor that prevents MDR-TB epidemics when TB treatment is poor. Any single population that successfully reduces its burden of drug-susceptible TB will have reduced herd immunity to externally or internally introduced strains of MDR-TB and can experience heightened vulnerability to an epidemic. Since countries with good TB control may be more vulnerable, their self interest dictates greater promotion of case detection and DOTS implementation in countries with poor control to control their risk of MDR-TB.

Epidemicity thresholds for water-borne and water-related diseases.

Science.gov (United States)

Mari, Lorenzo; Casagrandi, Renato; Rinaldo, Andrea; Gatto, Marino

2018-06-14

Determining the conditions that favor pathogen establishment in a host community is key to disease control and eradication. However, focusing on long-term dynamics alone may lead to an underestimation of the threats imposed by outbreaks triggered by short-term transient phenomena. Achieving an effective epidemiological response thus requires to look at different timescales, each of which may be endowed with specific management objectives. In this work we aim to determine epidemicity thresholds for some prototypical examples of water-borne and water-related diseases, a diverse family of infections transmitted either directly through water infested with pathogens or by vectors whose lifecycles are closely associated with water. From a technical perspective, while conditions for endemicity are determined via stability analysis, epidemicity thresholds are defined through generalized reactivity analysis, a recently proposed method that allows the study of the short-term instability properties of ecological systems. Understanding the drivers of water-borne and water-related disease dynamics over timescales that may be relevant to epidemic and/or endemic transmission is a challenge of the utmost importance, as large portions of the developing world are still struggling with the burden imposed by these infections. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Diabetes Epidemic in Korea

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Junghyun Noh

2016-09-01

Full Text Available Diabetes is one of the foremost public health issues worldwide that can lead to complications in many organ systems, and has become a significant cause of morbidity and mortality in Korea. According to data from the National Health Insurance Service (NHIS, about 2.7 million Koreans (8.0% aged 30 years or older had type 2 diabetes mellitus (T2DM in 2013. The prevalence of T2DM increased with age and rose from 5.6% in 2006 to 8.0% in 2013. Using data based on The Health Screening Service of the NHIS, 25% of Korean adults were reported to have prediabetes in 2013. The prevalence of an impaired fasting glucose tended to increase over time from 21.5% in 2006 to 25.0% in 2013. Even though nationwide health screening has been regularly conducted as a public service, the proportion of undiagnosed cases of diabetes was still reported to be on the higher side in the latest study. Based on the results of these epidemic studies, further actions will be needed to effectively implement lifestyle changes on a social level and increase measures for the early detection of diabetes to stem the tide of the epidemic.

Epidemics in Adaptive Social Networks with Temporary Link Deactivation

Science.gov (United States)

Tunc, Ilker; Shkarayev, Maxim S.; Shaw, Leah B.

2013-04-01

Disease spread in a society depends on the topology of the network of social contacts. Moreover, individuals may respond to the epidemic by adapting their contacts to reduce the risk of infection, thus changing the network structure and affecting future disease spread. We propose an adaptation mechanism where healthy individuals may choose to temporarily deactivate their contacts with sick individuals, allowing reactivation once both individuals are healthy. We develop a mean-field description of this system and find two distinct regimes: slow network dynamics, where the adaptation mechanism simply reduces the effective number of contacts per individual, and fast network dynamics, where more efficient adaptation reduces the spread of disease by targeting dangerous connections. Analysis of the bifurcation structure is supported by numerical simulations of disease spread on an adaptive network. The system displays a single parameter-dependent stable steady state and non-monotonic dependence of connectivity on link deactivation rate.

Defining and detecting malaria epidemics in south-east Iran

Directory of Open Access Journals (Sweden)

McKelvie William R

2012-03-01

Full Text Available Abstract Background A lack of consensus on how to define malaria epidemics has impeded the evaluation of early detection systems. This study aimed to develop local definitions of malaria epidemics in a known malarious area of Iran, and to use that definition to evaluate the validity of several epidemic alert thresholds. Methods Epidemic definition variables generated from surveillance data were plotted against weekly malaria counts to assess which most accurately labelled aberrations. Various alert thresholds were then generated from weekly counts or log counts. Finally, the best epidemic definition was used to calculate and compare sensitivities, specificities, detection delays, and areas under ROC curves of the alert thresholds. Results The best epidemic definition used a minimum duration of four weeks and week-specific and overall smoothed geometric means plus 1.0 standard deviation. It defined 13 epidemics. A modified C-SUM alert of untransformed weekly counts using a threshold of mean + 0.25 SD had the highest combined sensitivity and specificity. Untransformed C-SUM alerts also had the highest area under the ROC curve. Conclusions Defining local malaria epidemics using objective criteria facilitated the evaluation of alert thresholds. This approach needs further study to refine epidemic definitions and prospectively evaluate epidemic alerts.

Configuring the autism epidemic

DEFF Research Database (Denmark)

Seeberg, Jens; Christensen, Fie Lund Lindegaard

2017-01-01

Autism has been described as an epidemic, but this claim is contested and may point to an awareness epidemic, i.e. changes in the definition of what autism is and more attention being invested in diagnosis leading to a rise in registered cases. The sex ratio of children diagnosed with autism...... is skewed in favour of boys, and girls with autism tend to be diagnosed much later than boys. Building and further developing the notion of ‘configuration’ of epidemics, this article explores the configuration of autism in Denmark, with a particular focus on the health system and social support to families...... with children diagnosed with autism, seen from a parental perspective. The article points to diagnostic dynamics that contribute to explaining why girls with autism are not diagnosed as easily as boys. We unfold these dynamics through the analysis of a case of a Danish family with autism....

Reemergence of enterovirus 71 epidemic in northern Taiwan, 2012.

Science.gov (United States)

Luo, Shu-Ting; Chiang, Pai-Shan; Chung, Wan-Yu; Chia, Min-Yuan; Tsao, Kuo-Chien; Wang, Ying-Hsiang; Lin, Tzou-Yien; Lee, Min-Shi

2015-01-01

Enterovirus 71 (EV71) belongs to picornavirus family and could be classified phylogenetically into three major genogroups (A, B and C) including 11 genotypes (A, B1-B5 and C1-C5). Since 1997, EV71 has caused large-scale of epidemics with neurological complications in Asian children. In Taiwan, nationwide EV71 epidemics with different predominant genotypes have occurred cyclically since 1998. A nationwide EV71 epidemic occurred again in 2012. We conducted genetic and antigenic characterizations of the 2012 epidemic. Chang Gung Memorial Hospital (CGMH) is a medical center in northern Taiwan. In CGMH, specimens were collected from pediatric inpatients with suspected enterovirus infections for virus isolation. Enterovirus isolates were serotyped and genotyped and sera from EV71 inpatients were collected for measuring neutralizing antibody titers. There were 10, 16 and 99 EV71 inpatients identified in 2010, 2011 and 2012, respectively. There were 82 EV71 isolates genotyped, which identified 17 genotype C4a viruses and 65 genotype B5 viruses. The genotype B5 viruses were not detected until November 2011 and caused epidemics in 2012. Interestingly, the B5-2011 viruses were genetically distinguishable from the B5 viruses causing the 2008 epidemic and are likely introduced from China or Southeastern Asia. Based on antigenic analysis, minor antigenic variations were detected among the B5-2008, B5-2011, C4a-2008 and C4a-2012 viruses but these viruses antigenically differed from genotype A. Genotype B5 and C4a viruses antigenically differ from genotype A viruses which have disappeared globally for 30 years but have been detected in China since 2008. Enterovirus surveillance should monitor genetic and antigenic variations of EV71.

Generalization of positive and negative attitudes towards individuals to outgroup attitudes

NARCIS (Netherlands)

Stark, Tobias; Flache, Andreas; Veenstra, René

The generalization of attitudes toward individual outgroup members into attitudes toward the outgroup as a whole can affect intergroup relations. However, little is known about the relative strengths of the generalization of negative and positive interpersonal attitudes into attitudes about the

Unsynchronized influenza epidemics in two neighboring subtropical cities

Directory of Open Access Journals (Sweden)

Xiujuan Tang

2018-04-01

Full Text Available Objective: The aim of this study was to examine the synchrony of influenza epidemics between Hong Kong and Shenzhen, two neighboring subtropical cities in South China. Methods: Laboratory-confirmed influenza data for the period January 2006 to December 2016 were obtained from the Shenzhen Center for Disease Control and Prevention and the Department of Health in Hong Kong. The population data were retrieved from the 2011 population censuses. The weekly rates of laboratory-confirmed influenza cases were compared between Shenzhen and Hong Kong. Results: Unsynchronized influenza epidemics between Hong Kong and Shenzhen were frequently observed during the study period. Influenza A/H1N1 caused a more severe pandemic in Hong Kong in 2009, but the subsequent seasonal epidemics showed similar magnitudes in both cities. Two influenza A/H3N2 dominant epidemic waves were seen in Hong Kong in 2015, but these epidemics were very minor in Shenzhen. More influenza B epidemics occurred in Shenzhen than in Hong Kong. Conclusions: Influenza epidemics appeared to be unsynchronized between Hong Kong and Shenzhen most of the time. Given the close geographical locations of these two cities, this could be due to the strikingly different age structures of their populations. Keywords: Influenza epidemics, Synchrony, Shenzhen, Hong Kong

Networked SIS Epidemics With Awareness

KAUST Repository

Paarporn, Keith

2017-07-20

We study a susceptible-infected-susceptible epidemic process over a static contact network where the nodes have partial information about the epidemic state. They react by limiting their interactions with their neighbors when they believe the epidemic is currently prevalent. A node\\'s awareness is weighted by the fraction of infected neighbors in their social network, and a global broadcast of the fraction of infected nodes in the entire network. The dynamics of the benchmark (no awareness) and awareness models are described by discrete-time Markov chains, from which mean-field approximations (MFAs) are derived. The states of the MFA are interpreted as the nodes\\' probabilities of being infected. We show a sufficient condition for the existence of a

How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?

Science.gov (United States)

Mastrandrea, Rossana; Barrat, Alain

2016-06-01

Social interactions shape the patterns of spreading processes in a population. Techniques such as diaries or proximity sensors allow to collect data about encounters and to build networks of contacts between individuals. The contact networks obtained from these different techniques are however quantitatively different. Here, we first show how these discrepancies affect the prediction of the epidemic risk when these data are fed to numerical models of epidemic spread: low participation rate, under-reporting of contacts and overestimation of contact durations in contact diaries with respect to sensor data determine indeed important differences in the outcomes of the corresponding simulations with for instance an enhanced sensitivity to initial conditions. Most importantly, we investigate if and how information gathered from contact diaries can be used in such simulations in order to yield an accurate description of the epidemic risk, assuming that data from sensors represent the ground truth. The contact networks built from contact sensors and diaries present indeed several structural similarities: this suggests the possibility to construct, using only the contact diary network information, a surrogate contact network such that simulations using this surrogate network give the same estimation of the epidemic risk as simulations using the contact sensor network. We present and compare several methods to build such surrogate data, and show that it is indeed possible to obtain a good agreement between the outcomes of simulations using surrogate and sensor data, as long as the contact diary information is complemented by publicly available data describing the heterogeneity of the durations of human contacts.

Epidemic dynamics and endemic states in complex networks

Science.gov (United States)

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2001-06-01

We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below that the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are prone to the spreading and the persistence of infections whatever spreading rate the epidemic agents might possess. These results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks.

Epidemic dynamics and endemic states in complex networks

International Nuclear Information System (INIS)

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2001-01-01

We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below that the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are prone to the spreading and the persistence of infections whatever spreading rate the epidemic agents might possess. These results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks

Quarantine-generated phase transition in epidemic spreading.

Science.gov (United States)

Lagorio, C; Dickison, M; Vazquez, F; Braunstein, L A; Macri, P A; Migueles, M V; Havlin, S; Stanley, H E

2011-02-01

We study the critical effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible individuals protect themselves by disconnecting their links to infected neighbors with probability w and reconnecting them to other susceptible individuals chosen at random. Starting from a single infected individual, we show by an analytical approach and simulations that there is a phase transition at a critical rewiring (quarantine) threshold w(c) separating a phase (wspread out. We find that in our model the topology of the network strongly affects the size of the propagation and that w(c) increases with the mean degree and heterogeneity of the network. We also find that w(c) is reduced if we perform a preferential rewiring, in which the rewiring probability is proportional to the degree of infected nodes. ©2011 American Physical Society

Quarantine generated phase transition in epidemic spreading

Science.gov (United States)

Dicksion, Mark; Lagorio, Cecilia; Vazquez, F.; Braunstein, L.; Macri, P. A.; Migueles, M. V.; Havlin, S.; Stanley, H. E.

2011-03-01

We study the critical effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered (SIR) model in the presence of quarantine, where susceptible individuals protect themselves by disconnecting their links to infected neighbors with probability w, and reconnecting them to other susceptible individuals chosen at random. Starting from a single infected individual, we show by an analytical approach and simulations that there is a phase transition at a critical rewiring (quarantine) threshold wc separating a phase (w =wc) where the disease does not spread out. We find that in our model the topology of the network strongly affects the size of the propagation, and that wc increases with the mean degree and heterogeneity of the network. We also find that wc is reduced if we perform a preferential rewiring, in which the rewiring probability is proportional to the degree of infected nodes.

Phase Transitions of an Epidemic Spreading Model in Small-World Networks

Science.gov (United States)

Hua, Da-Yin; Gao, Ke

2011-06-01

We propose a modified susceptible-infected-refractory-susceptible (SIRS) model to investigate the global oscillations of the epidemic spreading in Watts—Strogatz (WS) small-world networks. It is found that when an individual immunity does not change or decays slowly in an immune period, the system can exhibit complex transition from an infecting stationary state to a large amplitude sustained oscillation or an absorbing state with no infection. When the immunity decays rapidly in the immune period, the transition to the global oscillation disappears and there is no oscillation. Furthermore, based on the spatio-temporal evolution patterns and the phase diagram, it is disclosed that a long immunity period takes an important role in the emergence of the global oscillation in small-world networks.

Optimal information dissemination strategy to promote preventive behaviors in multilayer epidemic networks.

Science.gov (United States)

Shakeri, Heman; Sahneh, Faryad Darabi; Scoglio, Caterina; Poggi-Corradini, Pietro; Preciado, Victor M

2015-06-01

Launching a prevention campaign to contain the spread of infection requires substantial financial investments; therefore, a trade-off exists between suppressing the epidemic and containing costs. Information exchange among individuals can occur as physical contacts (e.g., word of mouth, gatherings), which provide inherent possibilities of disease transmission, and non-physical contacts (e.g., email, social networks), through which information can be transmitted but the infection cannot be transmitted. Contact network (CN) incorporates physical contacts, and the information dissemination network (IDN) represents non-physical contacts, thereby generating a multilayer network structure. Inherent differences between these two layers cause alerting through CN to be more effective but more expensive than IDN. The constraint for an epidemic to die out derived from a nonlinear Perron-Frobenius problem that was transformed into a semi-definite matrix inequality and served as a constraint for a convex optimization problem. This method guarantees a dying-out epidemic by choosing the best nodes for adopting preventive behaviors with minimum monetary resources. Various numerical simulations with network models and a real-world social network validate our method.

Learning styles: individualizing computer-based learning environments

Directory of Open Access Journals (Sweden)

Tim Musson

1995-12-01

Full Text Available While the need to adapt teaching to the needs of a student is generally acknowledged (see Corno and Snow, 1986, for a wide review of the literature, little is known about the impact of individual learner-differences on the quality of learning attained within computer-based learning environments (CBLEs. What evidence there is appears to support the notion that individual differences have implications for the degree of success or failure experienced by students (Ford and Ford, 1992 and by trainee end-users of software packages (Bostrom et al, 1990. The problem is to identify the way in which specific individual characteristics of a student interact with particular features of a CBLE, and how the interaction affects the quality of the resultant learning. Teaching in a CBLE is likely to require a subset of teaching strategies different from that subset appropriate to more traditional environments, and the use of a machine may elicit different behaviours from those normally arising in a classroom context.

Phylodynamic analysis of HIV sub-epidemics in Mochudi, Botswana

Directory of Open Access Journals (Sweden)

Vlad Novitsky

2015-12-01

Real-time HIV genotyping and breaking down local HIV epidemics into phylogenetically distinct sub-epidemics may help to reveal the structure and dynamics of HIV transmission networks in communities, and aid in the design of targeted interventions for members of the acute sub-epidemics that likely fuel local HIV/AIDS epidemics.

Did the Food Environment Cause the Obesity Epidemic?

Science.gov (United States)

Hall, Kevin D

2018-01-01

Several putative explanations of the obesity epidemic relate to the changing food environment. Individual dietary macronutrients have each been theorized to be the prime culprit for population obesity, but these explanations are unlikely. Rather, obesity probably resulted from changes in the caloric quantity and quality of the food supply in concert with an industrialized food system that produced and marketed convenient, highly processed foods from cheap agricultural inputs. Such foods often contain high amounts of salt, sugar, fat, and flavor additives and are engineered to have supernormal appetitive properties driving increased consumption. Ubiquitous access to convenient and inexpensive food also changed normative eating behavior, with more people snacking, eating in restaurants, and spending less time preparing meals at home. While such changes in the food environment provide a likely explanation of the obesity epidemic, definitive scientific demonstration is hindered by the difficulty in experimentally isolating and manipulating important variables at the population level. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Emergence and control of epidemic meningococcal meningitis in sub-Saharan Africa.

Science.gov (United States)

Mohammed, Idris; Iliyasu, Garba; Habib, Abdulrazaq Garba

2017-02-01

For more than a century, meningitis epidemics have regularly recurred across sub-Saharan Africa, involving 19 contiguous countries that constitute a 'meningitis belt' where historically the causative agent has been serogroup A meningococcus. Attempts to control epidemic meningococcal meningitis in Africa by vaccination with meningococcal polysaccharide (PS) vaccines have not been successful. This is largely because PS vaccines are poorly immunogenic in young children, do not induce immunological memory, and have little or no effect on the pharyngeal carriage. Meningococcal PS-protein conjugate vaccines overcome these deficiencies. Conjugate meningococcal vaccine against serotype A (MenAfriVac) was developed between 2001 and 2009 and deployed in 2010. So far, 262 million individuals have been immunized across the meningitis belt. The public health benefits of MenAfriVac have already been demonstrated by a sharp decline in reported cases of meningococcal disease in the countries where it has been introduced. However, serogroup replacement following mass meningitis vaccination has been noted, and in 2015 an epidemic with a novel strain of serogroup C was recorded in Niger and Nigeria for the first time since 1975. This has posed a serious challenge toward elimination of meningococcal meningitis epidemics in the African. For an effective control of meningococcal meningitis in the African meningitis belt, there is a need for an effective surveillance system, provision of rapid antigen detection kits as well as affordable vaccine that provides protection against the main serogroups causing meningitis in the sub-region.

Prediction of meningococcal meningitis epidemics in western Africa by using climate information

Science.gov (United States)

YAKA, D. P.; Sultan, B.; Tarbangdo, F.; Thiaw, W. M.

2013-12-01

(particularly the meridional wind components) and seasonal recrudescence of MCM cases in order to elaborate seasonal occurrence of MCM epidemics prediction models on different spatiotemporal scales. These predictions have been experienced and evaluated by Burkina Meteorological Authority and Health Protection General Direction since 2009. The encouraging results from the monitoring and evaluation of these predictions given by such simple models enable the development of a monitoring and an early warning integrated system of MCM epidemics in Burkina Faso. This experience could be implemented in others African Sahelo-Soudanian countries.

Economic and Social Factors in Designing Disease Control Strategies for Epidemics on Networks

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Kleczkowski, A.; Dybiec, B.; Gilligan, C. A.

2006-11-01

Models for control of epidemics on local, global and small-world networks are considered, with only partial information accessible about the status of individuals and their connections. The main goal of an effective control measure is to stop the epidemic at a lowest possible cost, including treatment and cost necessary to track the disease spread. We show that delay in detection of infectious individuals and presence of long-range links are the most important factors determining the cost. However, the details of long-range links are usually the least-known element of the social interactions due to their occasional character and potentially short life-span. We show that under some conditions on the probability of disease spread, it is advisable to attempt to track those links, even if this involves additional costs. Thus, collecting some additional knowledge about the network structure might be beneficial to ensure a successful and cost-effective control.

Homo-psychologicus: Reactionary behavioural aspects of epidemics

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Alhaji Cherif

2016-03-01

Full Text Available We formulate an in silico model of pathogen avoidance mechanism and investigate its impact on defensive behavioural measures (e.g., spontaneous social exclusions and distancing, crowd avoidance and voluntary vaccination adaptation. In particular, we use SIR(BS (e.g., susceptible-infected-recovered with additional behavioural component model to investigate the impact of homo-psychologicus aspects of epidemics. We focus on reactionary behavioural changes, which apply to both social distancing and voluntary vaccination participations. Our analyses reveal complex relationships between spontaneous and uncoordinated behavioural changes, the emergence of its contagion properties, and mitigation of infectious diseases. We find that the presence of effective behavioural changes can impede the persistence of disease. Furthermore, it was found that under perfect effective behavioural change, there are three regions in the response factor (e.g., imitation and/or reactionary and behavioural scale factor (e.g., global/local factors ρ–α behavioural space. Mainly, (1 disease is always endemic even in the presence of behavioural change, (2 behavioural-prevalence plasticity is observed and disease can sometimes be eradication, and (3 elimination of endemic disease under permanence of permanent behavioural change is achieved. These results suggest that preventive behavioural changes (e.g., non-pharmaceutical prophylactic measures, social distancing and exclusion, crowd avoidance are influenced by individual differences in perception of risks and are a salient feature of epidemics. Additionally, these findings indicates that care needs to be taken when considering the effect of adaptive behavioural change in predicting the course of epidemics, and as well as the interpretation and development of the public health measures that account for spontaneous behavioural changes.

Homo-psychologicus: Reactionary behavioural aspects of epidemics.

Science.gov (United States)

Cherif, Alhaji; Barley, Kamal; Hurtado, Marcel

2016-03-01

We formulate an in silico model of pathogen avoidance mechanism and investigate its impact on defensive behavioural measures (e.g., spontaneous social exclusions and distancing, crowd avoidance and voluntary vaccination adaptation). In particular, we use SIR(B)S (e.g., susceptible-infected-recovered with additional behavioural component) model to investigate the impact of homo-psychologicus aspects of epidemics. We focus on reactionary behavioural changes, which apply to both social distancing and voluntary vaccination participations. Our analyses reveal complex relationships between spontaneous and uncoordinated behavioural changes, the emergence of its contagion properties, and mitigation of infectious diseases. We find that the presence of effective behavioural changes can impede the persistence of disease. Furthermore, it was found that under perfect effective behavioural change, there are three regions in the response factor (e.g., imitation and/or reactionary) and behavioural scale factor (e.g., global/local) factors ρ-α behavioural space. Mainly, (1) disease is always endemic even in the presence of behavioural change, (2) behavioural-prevalence plasticity is observed and disease can sometimes be eradication, and (3) elimination of endemic disease under permanence of permanent behavioural change is achieved. These results suggest that preventive behavioural changes (e.g., non-pharmaceutical prophylactic measures, social distancing and exclusion, crowd avoidance) are influenced by individual differences in perception of risks and are a salient feature of epidemics. Additionally, these findings indicates that care needs to be taken when considering the effect of adaptive behavioural change in predicting the course of epidemics, and as well as the interpretation and development of the public health measures that account for spontaneous behavioural changes. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

The Characteristics of TB Epidemic and TB/HIV Co-Infection Epidemic: A 2007-2013 Retrospective Study in Urumqi, Xinjiang Province, China.

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Wang Wei

Full Text Available This study was aimed to find out epidemiologic characteristic of tuberculosis (TB cases, and Human Immunodeficiency Virus (HIV positive cases among TB patients (TB/HIV co-infection through demographic, temporal, and spatial study in Urumqi.Descriptive statistics and multivariate logistic regression were applied to identify the epidemiologic characteristics and risk factors of TB epidemic and TB/HIV co-infection epidemic. All addresses of each TB case, TB/HIV co-infection case, and administrative street were transformed into geographical coordinate. Subsequently, the geocoded address for 82 streets was transformed into a dot map used as the basis of spatial datasets. In addition, the paper also used quantile map and the spatial scan statistic in order to identify the spatial distribution and spatial clusters of TB epidemic and TB/HIV co-infection epidemic.There was a declining trend of the notification rates of TB epidemic from 2007 to 2009, as well as a rising trend from 2010 to 2013. However, the notification rates of TB/HIV co-infection epidemic showed a rising trend from 2007 to 2010, and a declining trend from 2011 to 2013. Moreover, a significant share of TB epidemic and TB/HIV co-infection epidemic happened between the age of 15 to 45 years old, indicating an increase in risk of TB and TB/HIV infection. It is worth noting that the risk of HIV infection for male TB patients was 2.947 times (95% CI [2.178, 3.988] than that of female patients. Han ethnicity and Uygur ethnicity in urban region accounted for a large proportion of total TB and TB/HIV co-infection cases. Most of the TB cases of minorities in Urumqi showed a statistically significant increase in risk of HIV infection than Han ethnicity in Urumqi. In addition, the spatial distribution of TB epidemic and TB/HIV co-infection epidemic was highly skewed. Most of the local clusters were located in urban area and rural-urban continuum where showed an increase in risk of TB and TB

Understanding Ebola: the 2014 epidemic.

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Kaner, Jolie; Schaack, Sarah

2016-09-13

Near the end of 2013, an outbreak of Zaire ebolavirus (EBOV) began in Guinea, subsequently spreading to neighboring Liberia and Sierra Leone. As this epidemic grew, important public health questions emerged about how and why this outbreak was so different from previous episodes. This review provides a synthetic synopsis of the 2014-15 outbreak, with the aim of understanding its unprecedented spread. We present a summary of the history of previous epidemics, describe the structure and genetics of the ebolavirus, and review our current understanding of viral vectors and the latest treatment practices. We conclude with an analysis of the public health challenges epidemic responders faced and some of the lessons that could be applied to future outbreaks of Ebola or other viruses.

Timing of the HIV-1 subtype C epidemic in Ethiopia based on early virus strains and subsequent virus diversification

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Abebe, A.; Lukashov, V. V.; Pollakis, G.; Kliphuis, A.; Fontanet, A. L.; Goudsmit, J.; Rinke de Wit, T. F.

2001-01-01

OBJECTIVE: To trace the introduction of HIV-1 subtype C into Ethiopia based on virus diversification during the epidemic. DESIGN: A set of 474 serum samples obtained in Ethiopia in 1982-1985 was tested for HIV-1. HIV-1 env gp120 V3 and gag or pol regions were sequenced and analysed together with

Inferring epidemic contact structure from phylogenetic trees.

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Gabriel E Leventhal

Full Text Available Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing.

Malaria epidemic and drug resistance, Djibouti.

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Rogier, Christophe; Pradines, Bruno; Bogreau, H; Koeck, Jean-Louis; Kamil, Mohamed-Ali; Mercereau-Puijalon, Odile

2005-02-01

Analysis of Plasmodium falciparum isolates collected before, during, and after a 1999 malaria epidemic in Djibouti shows that, despite a high prevalence of resistance to chloroquine, the epidemic cannot be attributed to a sudden increase in drug resistance of local parasite populations.

The psychiatric epidemic in the American workplace.

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Brodsky, C M

1988-01-01

Several characteristics help distinguish MPI in the workplace from illness outbreaks due to physical causes: no laboratory or physical findings confirming an specific organic cause evidence of specific physical or psychological stressors victims are mostly women and those of lower socioeconomic status in the workplace hyperventilation-type symptoms are prominent apparent transmission by audiovisual cues rapid spread of the illness followed by rapid remission of symptoms, unless symptoms are fixed by physicians and litigation benign morbidity If a physical or chemical cause of the illness is not obvious and if episodes recur, the illness remains a mystery and the workplace becomes a breeding ground for anxiety, confusion, fear, and rumor. Economic pressures to resume normal operations are counteracted by fears that an environmental contaminant still exists. Once all physical explanations have been ruled out, investigators may turn to psychological explanations and focus on mass hysteria, but that explanation is primarily based on the absence of physical evidence rather than the presence of agreed-upon psychosocial conditions. Some reports suggest that the diagnosis of MPI is really an excuse for not conducting an adequate evaluation of low-level environmental contaminants. The disability in some workers is prolonged and points to non-work-related factors that may be contributing. Were it not for the unverifiable physical complaints and the workers' insistence that the symptoms are the result of physical disease and their concern about the complaints and their reactions to dismissal of their complaints, we would not consider these patients to have a mental disorder. These individuals are reinforced in their beliefs by some physicians and attorneys, and resultant litigation tends to fix their symptoms. In fact, a "conspiracy theory" evolves when there are enough convinced people--and enough people trying to dissuade them. Group phenomena reinforce their beliefs and

Existence, uniqueness, monotonicity and asymptotic behaviour of travelling waves for epidemic models

International Nuclear Information System (INIS)

Hsu, Cheng-Hsiung; Yang, Tzi-Sheng

2013-01-01

The purpose of this work is to investigate the existence, uniqueness, monotonicity and asymptotic behaviour of travelling wave solutions for a general epidemic model arising from the spread of an epidemic by oral–faecal transmission. First, we apply Schauder's fixed point theorem combining with a supersolution and subsolution pair to derive the existence of positive monotone monostable travelling wave solutions. Then, applying the Ikehara's theorem, we determine the exponential rates of travelling wave solutions which converge to two different equilibria as the moving coordinate tends to positive infinity and negative infinity, respectively. Finally, using the sliding method, we prove the uniqueness result provided the travelling wave solutions satisfy some boundedness conditions. (paper)

Recalibrating disease parameters for increasing realism in modeling epidemics in closed settings

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Livio Bioglio

2016-11-01

Full Text Available Abstract Background The homogeneous mixing assumption is widely adopted in epidemic modelling for its parsimony and represents the building block of more complex approaches, including very detailed agent-based models. The latter assume homogeneous mixing within schools, workplaces and households, mostly for the lack of detailed information on human contact behaviour within these settings. The recent data availability on high-resolution face-to-face interactions makes it now possible to assess the goodness of this simplified scheme in reproducing relevant aspects of the infection dynamics. Methods We consider empirical contact networks gathered in different contexts, as well as synthetic data obtained through realistic models of contacts in structured populations. We perform stochastic spreading simulations on these contact networks and in populations of the same size under a homogeneous mixing hypothesis. We adjust the epidemiological parameters of the latter in order to fit the prevalence curve of the contact epidemic model. We quantify the agreement by comparing epidemic peak times, peak values, and epidemic sizes. Results Good approximations of the peak times and peak values are obtained with the homogeneous mixing approach, with a median relative difference smaller than 20 % in all cases investigated. Accuracy in reproducing the peak time depends on the setting under study, while for the peak value it is independent of the setting. Recalibration is found to be linear in the epidemic parameters used in the contact data simulations, showing changes across empirical settings but robustness across groups and population sizes. Conclusions An adequate rescaling of the epidemiological parameters can yield a good agreement between the epidemic curves obtained with a real contact network and a homogeneous mixing approach in a population of the same size. The use of such recalibrated homogeneous mixing approximations would enhance the accuracy and

Recalibrating disease parameters for increasing realism in modeling epidemics in closed settings.

Science.gov (United States)

Bioglio, Livio; Génois, Mathieu; Vestergaard, Christian L; Poletto, Chiara; Barrat, Alain; Colizza, Vittoria

2016-11-14

The homogeneous mixing assumption is widely adopted in epidemic modelling for its parsimony and represents the building block of more complex approaches, including very detailed agent-based models. The latter assume homogeneous mixing within schools, workplaces and households, mostly for the lack of detailed information on human contact behaviour within these settings. The recent data availability on high-resolution face-to-face interactions makes it now possible to assess the goodness of this simplified scheme in reproducing relevant aspects of the infection dynamics. We consider empirical contact networks gathered in different contexts, as well as synthetic data obtained through realistic models of contacts in structured populations. We perform stochastic spreading simulations on these contact networks and in populations of the same size under a homogeneous mixing hypothesis. We adjust the epidemiological parameters of the latter in order to fit the prevalence curve of the contact epidemic model. We quantify the agreement by comparing epidemic peak times, peak values, and epidemic sizes. Good approximations of the peak times and peak values are obtained with the homogeneous mixing approach, with a median relative difference smaller than 20 % in all cases investigated. Accuracy in reproducing the peak time depends on the setting under study, while for the peak value it is independent of the setting. Recalibration is found to be linear in the epidemic parameters used in the contact data simulations, showing changes across empirical settings but robustness across groups and population sizes. An adequate rescaling of the epidemiological parameters can yield a good agreement between the epidemic curves obtained with a real contact network and a homogeneous mixing approach in a population of the same size. The use of such recalibrated homogeneous mixing approximations would enhance the accuracy and realism of agent-based simulations and limit the intrinsic biases of

Identifying multiple influential spreaders based on generalized closeness centrality

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Liu, Huan-Li; Ma, Chuang; Xiang, Bing-Bing; Tang, Ming; Zhang, Hai-Feng

2018-02-01

To maximize the spreading influence of multiple spreaders in complex networks, one important fact cannot be ignored: the multiple spreaders should be dispersively distributed in networks, which can effectively reduce the redundance of information spreading. For this purpose, we define a generalized closeness centrality (GCC) index by generalizing the closeness centrality index to a set of nodes. The problem converts to how to identify multiple spreaders such that an objective function has the minimal value. By comparing with the K-means clustering algorithm, we find that the optimization problem is very similar to the problem of minimizing the objective function in the K-means method. Therefore, how to find multiple nodes with the highest GCC value can be approximately solved by the K-means method. Two typical transmission dynamics-epidemic spreading process and rumor spreading process are implemented in real networks to verify the good performance of our proposed method.

A mechanistic spatio-temporal framework for modelling individual-to-individual transmission-With an application to the 2014-2015 West Africa Ebola outbreak.

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Max S Y Lau

2017-10-01

Full Text Available In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015. Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging.

A mechanistic spatio-temporal framework for modelling individual-to-individual transmission—With an application to the 2014-2015 West Africa Ebola outbreak

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McClelland, Amanda; Zelner, Jon; Streftaris, George; Funk, Sebastian; Metcalf, Jessica; Dalziel, Benjamin D.; Grenfell, Bryan T.

2017-01-01

In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging. PMID:29084216

Addressing men and gender diversity in education: a promising solution to the HIV/AIDS epidemic.

Science.gov (United States)

Ghajarieh, Amir Biglar Beigi; Kow, Karen Yip Cheng

2011-04-01

To date, researchers investigating gender in relation to social issues underscore women and appear to sideline men. Focusing on women in studies concerning sociogender issues may exclude not only men from mainstream research, but also those who do not fit into the binary gender system, including gay, lesbian, bisexual, and transgender (GLBT) people. One area closely related to gender issues is the HIV epidemic. Mainstream discussions of men and other versions of masculinity and femininity including GLBT people in the gender-related studies of the HIV epidemic can decrease the vulnerability of individuals against HIV infections regardless of their biological sex.

Competing spreading processes on multiplex networks: awareness and epidemics.

Science.gov (United States)

Granell, Clara; Gómez, Sergio; Arenas, Alex

2014-07-01

Epidemiclike spreading processes on top of multilayered interconnected complex networks reveal a rich phase diagram of intertwined competition effects. A recent study by the authors [C. Granell et al., Phys. Rev. Lett. 111, 128701 (2013).] presented an analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the spreading of information awareness to prevent infection, on top of multiplex networks. The results in the case in which awareness implies total immunization to the disease revealed the existence of a metacritical point at which the critical onset of the epidemics starts, depending on completion of the awareness process. Here we present a full analysis of these critical properties in the more general scenario where the awareness spreading does not imply total immunization, and where infection does not imply immediate awareness of it. We find the critical relation between the two competing processes for a wide spectrum of parameters representing the interaction between them. We also analyze the consequences of a massive broadcast of awareness (mass media) on the final outcome of the epidemic incidence. Importantly enough, the mass media make the metacritical point disappear. The results reveal that the main finding, i.e., existence of a metacritical point, is rooted in the competition principle and holds for a large set of scenarios.

Ten Putative Contributors to the Obesity Epidemic

Science.gov (United States)

McAllister, Emily J.; Dhurandhar, Nikhil V.; Keith, Scott W.; Aronne, Louis J.; Barger, Jamie; Baskin, Monica; Benca, Ruth M.; Biggio, Joseph; Boggiano, Mary M.; Eisenmann, Joe C.; Elobeid, Mai; Fontaine, Kevin R.; Gluckman, Peter; Hanlon, Erin C.; Katzmarzyk, Peter; Pietrobelli, Angelo; Redden, David T.; Ruden, Douglas M.; Wang, Chenxi; Waterland, Robert A.; Wright, Suzanne M.; Allison, David B.

2010-01-01

The obesity epidemic is a global issue and shows no signs of abating, while the cause of this epidemic remains unclear. Marketing practices of energy-dense foods and institutionally-driven declines in physical activity are the alleged perpetrators for the epidemic, despite a lack of solid evidence to demonstrate their causal role. While both may contribute to obesity, we call attention to their unquestioned dominance in program funding and public efforts to reduce obesity, and propose several alternative putative contributors that would benefit from equal consideration and attention. Evidence for microorganisms, epigenetics, increasing maternal age, greater fecundity among people with higher adiposity, assortative mating, sleep debt, endocrine disruptors, pharmaceutical iatrogenesis, reduction in variability of ambient temperatures, and intrauterine and intergenerational effects, as contributing factors to the obesity epidemic are reviewed herein. While the evidence is strong for some contributors such as pharmaceutical-induced weight gain, it is still emerging for other reviewed factors. Considering the role of such putative etiological factors of obesity may lead to comprehensive, cause specific, and effective strategies for prevention and treatment of this global epidemic. PMID:19960394

Epidemics and agendas: the politics of nightly news coverage of AIDS.

Science.gov (United States)

Colby, D C; Cook, T E

1991-01-01

We examine why the exponential growth of AIDS cases or the wide-spread professional perception of a health crisis did not move the epidemic more quickly onto the agenda of public problems. One possible explanation focuses on how the national news media's construction of AIDS shaped the meaning of the epidemic for mass and elite audiences. An examination of nightly news coverage by the three major networks from 1982 to 1989 reveals considerable variability and volatility in their coverage. Topic-driven saturation coverage occurred only during three short periods in 1983, 1985, and 1987, when the epidemic seemed likely to affect the "general population". Only at such moments did public opinion shift and discussion and debate in government begin. Otherwise, the typical AIDS story tended less to sensationalize than to reassure, largely because journalists depended upon government officials and high-ranking doctors to present them with evidence of news. Such sources had interests either in avoiding coverage or in pointing toward breakthroughs; more critical sources, especially within the gay movement, had far less access to the news. In concluding, we considered the prospects and pitfalls of the news media's power to shape the public agenda.

Global stability of an SEIR epidemic model with constant immigration

Energy Technology Data Exchange (ETDEWEB)

Li Guihua [Key Laboratory of Eco-environments in Three Gorges Reservoir Region (Ministry of Education), Faculty of Life Science, Southwest China Normal University, Chongqing 400715 (China) and Department of Mathematics, Southwest China Normal University, Chongqing 400715 (China) and Department of Mathematics, North University of China, Taiyuan Shanxi 030051 (China)]. E-mail: liguihua@nuc.edu.cn; Wang Wendi [Department of Mathematics, Southwest China Normal University, Chongqing 400715 (China); Jin Zhen [Department of Mathematics, North University of China, Taiyuan Shanxi 030051 (China)

2006-11-15

An SEIR epidemic model with the infectious force in the latent (exposed), infected and recovered period is studied. It is assumed that susceptible and exposed individuals have constant immigration rates. The model exhibits a unique endemic state if the fraction p of infectious immigrants is positive. If the basic reproduction number R is greater than 1, sufficient conditions for the global stability of the endemic equilibrium are obtained by the compound matrix theory.

Global stability of an SEIR epidemic model with constant immigration

International Nuclear Information System (INIS)

Li Guihua; Wang Wendi; Jin Zhen

2006-01-01

An SEIR epidemic model with the infectious force in the latent (exposed), infected and recovered period is studied. It is assumed that susceptible and exposed individuals have constant immigration rates. The model exhibits a unique endemic state if the fraction p of infectious immigrants is positive. If the basic reproduction number R is greater than 1, sufficient conditions for the global stability of the endemic equilibrium are obtained by the compound matrix theory

Predicting and Evaluating the Epidemic Trend of Ebola Virus Disease in the 2014-2015 Outbreak and the Effects of Intervention Measures.

Directory of Open Access Journals (Sweden)

Zuiyuan Guo

Full Text Available We constructed dynamic Ebola virus disease (EVD transmission models to predict epidemic trends and evaluate intervention measure efficacy following the 2014 EVD epidemic in West Africa. We estimated the effective vaccination rate for the population, with basic reproduction number (R0 as the intermediate variable. Periodic EVD fluctuation was analyzed by solving a Jacobian matrix of differential equations based on a SIR (susceptible, infective, and removed model. A comprehensive compartment model was constructed to fit and predict EVD transmission patterns, and to evaluate the effects of control and prevention measures. Effective EVD vaccination rates were estimated to be 42% (31-50%, 45% (42-48%, and 51% (44-56% among susceptible individuals in Guinea, Liberia and Sierra Leone, respectively. In the absence of control measures, there would be rapid mortality in these three countries, and an EVD epidemic would be likely recur in 2035, and then again 8~9 years later. Oscillation intervals would shorten and outbreak severity would decrease until the periodicity reached ~5.3 years. Measures that reduced the spread of EVD included: early diagnosis, treatment in isolation, isolating/monitoring close contacts, timely corpse removal, post-recovery condom use, and preventing or quarantining imported cases. EVD may re-emerge within two decades without control and prevention measures. Mass vaccination campaigns and control and prevention measures should be instituted to prevent future EVD epidemics.

Shifting Patterns of the HIV Epidemic in Southwest China: A Case Study Based on Sentinel Surveillance, 1995-2012.

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Chow, Eric P F; Gao, Liangmin; Chen, Liang; Jing, Jun; Zhang, Lei

2015-06-01

The HIV epidemic is experiencing a rapid shift in transmission profile in China. This study aims to examine the changes in magnitude, transmission pattern, and trend of the HIV epidemic in a typical Southwest Chinese prefecture over the period of 1995-2012. HIV surveillance data from the web-based reporting system were analyzed during this period. We investigated the temporal trends in the changing characteristics of HIV transmission, the HIV disease burden in key affected populations, and assessed the impacts on HIV disease progression due to scale-up of antiretroviral treatment. A total of 3556 HIV/AIDS cases were reported in Yuxi prefecture, Yunnan, over the study period. The number of HIV tests conducted has dramatically increased from 1041 in 1995 to 247,859 in 2012, resulting in a substantial increase in HIV diagnoses from 11 cases to 327 cases over the same period. Since 2005, cumulatively 1250 eligible people living with HIV (PLHIV) have received combination antiretroviral therapy which reduced AIDS disease progression from 9.0% (95% CI: 6.7-11.4%) in 1995 to 0.1% (0-0.3%) in 2012 (ptrend=0.0002). The primary mode of HIV transmission has been shifted from injection sharing (71.9% diagnoses in 1995-2004) to unsafe sexual contacts (82.6% diagnoses in 2012). Yuxi prefecture is experiencing a concentrated but shifting HIV epidemic. Scale-up of HIV testing is essential to effective sentinel surveillance and enhancing early diagnosis and treatment in PLHIV.

Cooperation dynamics of generalized reciprocity in state-based social dilemmas

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Stojkoski, Viktor; Utkovski, Zoran; Basnarkov, Lasko; Kocarev, Ljupco

2018-05-01

We introduce a framework for studying social dilemmas in networked societies where individuals follow a simple state-based behavioral mechanism based on generalized reciprocity, which is rooted in the principle "help anyone if helped by someone." Within this general framework, which applies to a wide range of social dilemmas including, among others, public goods, donation, and snowdrift games, we study the cooperation dynamics on a variety of complex network examples. By interpreting the studied model through the lenses of nonlinear dynamical systems, we show that cooperation through generalized reciprocity always emerges as the unique attractor in which the overall level of cooperation is maximized, while simultaneously exploitation of the participating individuals is prevented. The analysis elucidates the role of the network structure, here captured by a local centrality measure which uniquely quantifies the propensity of the network structure to cooperation by dictating the degree of cooperation displayed both at the microscopic and macroscopic level. We demonstrate the applicability of the analysis on a practical example by considering an interaction structure that couples a donation process with a public goods game.

Food system consequences of a fungal disease epidemic in a major crop.

Science.gov (United States)

Godfray, H Charles J; Mason-D'Croz, Daniel; Robinson, Sherman

2016-12-05

Fungal diseases are major threats to the most important crops upon which humanity depends. Were there to be a major epidemic that severely reduced yields, its effects would spread throughout the globalized food system. To explore these ramifications, we use a partial equilibrium economic model of the global food system (IMPACT) to study a hypothetical severe but short-lived epidemic that reduces rice yields in the countries affected by 80%. We modelled a succession of epidemic scenarios of increasing severity, starting with the disease in a single country in southeast Asia and ending with the pathogen present in most of eastern Asia. The epidemic and subsequent crop losses led to substantially increased global rice prices. However, as long as global commodity trade was unrestricted and able to respond fast enough, the effects on individual calorie consumption were, to a large part, mitigated. Some of the worse effects were projected to be experienced by poor net-rice importing countries in sub-Saharan Africa, which were not affected directly by the disease but suffered because of higher rice prices. We critique the assumptions of our models and explore political economic pressures to restrict trade at times of crisis. We finish by arguing for the importance of 'stress-testing' the resilience of the global food system to crop disease and other shocks.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'. © 2016 The Author(s).

Modeling historical tuberculosis epidemics among Canadian First Nations: effects of malnutrition and genetic variation

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Sarah F. Ackley

2015-09-01

Full Text Available Late 19th century epidemics of tuberculosis (TB in Western Canadian First Nations resulted in peak TB mortality rates more than six times the highest rates recorded in Europe. Using a mathematical modeling approach and historical TB mortality time series, we investigate potential causes of high TB mortality and rapid epidemic decline in First Nations from 1885 to 1940. We explore two potential causes of dramatic epidemic dynamics observed in this setting: first, we explore effects of famine prior to 1900 on both TB and population dynamics. Malnutrition is recognized as an individual-level risk factor for TB progression and mortality; its population-level effects on TB epidemics have not been explored previously. Second, we explore effects of heterogeneity in susceptibility to TB in two ways: modeling heterogeneity in susceptibility to infection, and heterogeneity in risk of developing disease once infected. Our results indicate that models lacking famine-related changes in TB parameters or heterogeneity result in an implausibly poor fit to both the TB mortality time series and census data; the inclusion of these features allows for the characteristic decline and rise in population observed in First Nations during this time period and confers improved fits to TB mortality data.

A Bayesian method for inferring transmission chains in a partially observed epidemic.

Energy Technology Data Exchange (ETDEWEB)

Marzouk, Youssef M.; Ray, Jaideep

2008-10-01

We present a Bayesian approach for estimating transmission chains and rates in the Abakaliki smallpox epidemic of 1967. The epidemic affected 30 individuals in a community of 74; only the dates of appearance of symptoms were recorded. Our model assumes stochastic transmission of the infections over a social network. Distinct binomial random graphs model intra- and inter-compound social connections, while disease transmission over each link is treated as a Poisson process. Link probabilities and rate parameters are objects of inference. Dates of infection and recovery comprise the remaining unknowns. Distributions for smallpox incubation and recovery periods are obtained from historical data. Using Markov chain Monte Carlo, we explore the joint posterior distribution of the scalar parameters and provide an expected connectivity pattern for the social graph and infection pathway.

Impact of delay on disease outbreak in a spatial epidemic model

Science.gov (United States)

Zhao, Xia-Xia; Wang, Jian-Zhong

2015-04-01

One of the central issues in studying epidemic spreading is the mechanism on disease outbreak. In this paper, we investigate the effects of time delay on disease outbreak in spatial epidemics based on a reaction-diffusion model. By mathematical analysis and numerical simulations, we show that when time delay is more than a critical value, the disease outbreaks. The obtained results show that the time delay is an important factor in the spread of the disease, which may provide new insights on disease control.

Epidemic Spreading in Complex Networks with Resilient Nodes: Applications to FMD

Directory of Open Access Journals (Sweden)

Pilwon Kim

2018-01-01

Full Text Available At the outbreak of the animal epidemic disease, farms that recover quickly from partially infected state can delay or even suppress the wide spreading of the infection over farm networks. In this work, we focus on how the spatial transmission of the infection is affected by both factors, the topology of networks and the internal resilience mechanism of nodes. We first develop an individual farm model to examine the influence of initial number of infected individuals and vaccination rate on the transmission in a single farm. Based on such intrafarm model, the farm network is constructed which reflects disease transmission between farms at various stages. We explore the impact of the farms vaccinated at low rates on the disease transmission into entire farm network and investigate the effect of the control on hub farms on the transmission over the farm network. It is shown that intensive control on the farms vaccinated at low rates and hub farms effectively reduces the potential risk of foot-and-mouth disease (FMD outbreak on the farm network.

HIV epidemics in Shenzhen and Chongqing, China.

Directory of Open Access Journals (Sweden)

Shu Yang

Full Text Available Men who have sex with men (MSM and heterosexuals are the populations with the fastest growing HIV infection rates in China. We characterize the epidemic growth and age patterns between these two routes from 2004 to 2015 in Chongqing and Shenzhen, China.Data were downloaded from the National HIV/ AIDS Comprehensive Response Information Management System. For the new HIV diagnoses of heterosexuals and MSM in both cities, we estimated the growth rates by fitting different sub-exponential models. Heat maps are used to show their age patterns. We used histograms to compare these patterns by birth cohort.The MSM epidemics grew significantly in both cities. Chongqing experienced quadratic growth in HIV reported cases with an estimated growth rate of 0.086 per week and a "deceleration rate" of 0.673. HIV reported cases of MSM in Shenzhen grew even more drastically with a growth rate of 0.033 per week and "deceleration rate" of 0.794. The new infections are mainly affecting the ages of 18 to 30 in Chongqing and ages of 20 to 35 in Shenzhen. They peaked in early 1990's and mid-1990's birth cohorts in Chongqing and Shenzhen respectively. The HIV epidemic among heterosexuals grew rapidly in both cities. The growth rates were estimated as 0.02 and 0.028 in Chongqing and Shenzhen respectively whereas the "deceleration rates" were 0.878 and 0.790 in these two places. It affected mostly aged 18 to 75 in males and 18 to 65 in females in Chongqing and aged 18 to 45 in males and 18 to 50 in females in Shenzhen in 2015. In Chongqing, the heterosexual female epidemics display two peaks in HIV diagnoses in the birth cohorts of early 1950's and early 1980's, with heterosexual male epidemics peaked in early 1940's and early 1960's. The heterosexual male and female epidemics display higher rates in the birth cohort 1940-1960, than the birth cohort 1960-1990. It peaked in birth cohorts of 1950's and 1980's in Shenzhen.We revealed striking differences in epidemic growth

Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks.

Science.gov (United States)

Onaga, Tomokatsu; Gleeson, James P; Masuda, Naoki

2017-09-08

Social contact networks underlying epidemic processes in humans and animals are highly dynamic. The spreading of infections on such temporal networks can differ dramatically from spreading on static networks. We theoretically investigate the effects of concurrency, the number of neighbors that a node has at a given time point, on the epidemic threshold in the stochastic susceptible-infected-susceptible dynamics on temporal network models. We show that network dynamics can suppress epidemics (i.e., yield a higher epidemic threshold) when the node's concurrency is low, but can also enhance epidemics when the concurrency is high. We analytically determine different phases of this concurrency-induced transition, and confirm our results with numerical simulations.

Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks

Science.gov (United States)

Onaga, Tomokatsu; Gleeson, James P.; Masuda, Naoki

2017-09-01

Social contact networks underlying epidemic processes in humans and animals are highly dynamic. The spreading of infections on such temporal networks can differ dramatically from spreading on static networks. We theoretically investigate the effects of concurrency, the number of neighbors that a node has at a given time point, on the epidemic threshold in the stochastic susceptible-infected-susceptible dynamics on temporal network models. We show that network dynamics can suppress epidemics (i.e., yield a higher epidemic threshold) when the node's concurrency is low, but can also enhance epidemics when the concurrency is high. We analytically determine different phases of this concurrency-induced transition, and confirm our results with numerical simulations.

Dynamic malware containment under an epidemic model with alert

Science.gov (United States)

Zhang, Tianrui; Yang, Lu-Xing; Yang, Xiaofan; Wu, Yingbo; Tang, Yuan Yan

2017-03-01

Alerting at the early stage of malware invasion turns out to be an important complement to malware detection and elimination. This paper addresses the issue of how to dynamically contain the prevalence of malware at a lower cost, provided alerting is feasible. A controlled epidemic model with alert is established, and an optimal control problem based on the epidemic model is formulated. The optimality system for the optimal control problem is derived. The structure of an optimal control for the proposed optimal control problem is characterized under some conditions. Numerical examples show that the cost-efficiency of an optimal control strategy can be enhanced by adjusting the upper and lower bounds on admissible controls.

Digital Health Communication and Global Public Influence: A Study of the Ebola Epidemic.

Science.gov (United States)

Roberts, Hal; Seymour, Brittany; Fish, Sands Alden; Robinson, Emily; Zuckerman, Ethan

2017-01-01

Scientists and health communication professionals expressed frustration over the relationship between misinformation circulating on the Internet and global public perceptions of and responses to the Ebola epidemic originating in West Africa. Using the big data platform Media Cloud, we analyzed all English-language stories about keyword "Ebola" published from 1 July 2014 to 17 November 2014 from the media sets U.S. Mainstream Media, U.S. Regional Media, U.S. Political Blogs, U.S. Popular Blogs, Europe Media Monitor, and Global Voices to understand how social network theory and models of the networked global public may have contributed to health communication efforts. 109,400 stories met our inclusion criteria. The CDC and WHO were the two media sources with the most inlinks (hyperlinks directed to their sites). Twitter was fourth Significantly more public engagement on social media globally was directed toward stories about risks of U.S. domestic Ebola infections than toward stories focused on Ebola infections in West Africa or on science-based information. Corresponding public sentiments about Ebola were reflected in the policy responses of the international community, including violations of the International Health Regulations and the treatment of potentially exposed individuals. The digitally networked global public may have influenced the discourse, sentiment, and response to the Ebola epidemic.

Public health interventions for epidemics: implications for multiple infection waves.

Science.gov (United States)

Wessel, Lindsay; Hua, Yi; Wu, Jianhong; Moghadas, Seyed M

2011-02-25

Epidemics with multiple infection waves have been documented for some human diseases, most notably during past influenza pandemics. While pathogen evolution, co-infection, and behavioural changes have been proposed as possible mechanisms for the occurrence of subsequent outbreaks, the effect of public health interventions remains undetermined. We develop mean-field and stochastic epidemiological models for disease transmission, and perform simulations to show how control measures, such as drug treatment and isolation of ill individuals, can influence the epidemic profile and generate sequences of infection waves with different characteristics. We demonstrate the impact of parameters representing the effectiveness and adverse consequences of intervention measures, such as treatment and emergence of drug resistance, on the spread of a pathogen in the population. If pathogen resistant strains evolve under drug pressure, multiple outbreaks are possible with variability in their characteristics, magnitude, and timing. In this context, the level of drug use and isolation capacity play an important role in the occurrence of subsequent outbreaks. Our simulations for influenza infection as a case study indicate that the intensive use of these interventions during the early stages of the epidemic could delay the spread of disease, but it may also result in later infection waves with possibly larger magnitudes. The findings highlight the importance of intervention parameters in the process of public health decision-making, and in evaluating control measures when facing substantial uncertainty regarding the epidemiological characteristics of an emerging infectious pathogen. Critical factors that influence population health including evolutionary responses of the pathogen under the pressure of different intervention measures during an epidemic should be considered for the design of effective strategies that address short-term targets compatible with long-term disease outcomes.

Increasing survival time decreases the cost-effectiveness of using "test & treat'' to eliminate HIV epidemics.

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Wagner, Bradley G; Coburn, Brian J; Blower, Sally

2013-01-01

Treating HIV-infected individuals reduces their viral load, consequently increasing their survival time and decreasing their infectivity. It has been proposed that universal testing and treatment (i.e., universal "test & treat'') could lead to HIV elimination and would be extremely cost-effective. It is now being debated whether to use a universal "test & treat'' approach in the "real-world'' as a prevention strategy to control HIV epidemics. However current modeling predictions of the impact, and cost-effectiveness, of universal `"est & treat'' strategies are based on an unrealistically short survival time for treated individuals. Here we use mathematical modeling and a longer, more realistic, survival time. We model the potential impact of a universal "test & treat'' strategy in South Africa. Our results show that increasing the length of the survival time on treatment, although beneficial to individuals, reduces the probability of eliminating HIV and decreases the cost-effectiveness of using universal "test & treat'' strategies. Therefore our results show that individual-level benefits and public health benefits will conflict when using "test &treat'' strategies to reduce HIV transmission.

Epidemics: Lessons from the past and current patterns of response

Science.gov (United States)

Martin, Paul

2008-09-01

Hippocrates gave the term 'epidemic' its medical meaning. From antiquity to modern times, the meaning of the word epidemic has continued to evolve. Over the centuries, researchers have reached an understanding of the varying aspects of epidemics and have tried to combat them. The role played by travel, trade, and human exchanges in the propagation of epidemic infectious diseases has been understood. In 1948, the World Health Organization was created and given the task of advancing ways of combating epidemics. An early warning system to combat epidemics has been implemented by the WHO. The Global Outbreak Alert and Response Network (GOARN) is collaboration between existing institutions and networks that pool their human and technical resources to fight outbreaks. Avian influenza constitutes currently the most deadly epidemic threat, with fears that it could rapidly reach pandemic proportions and put several thousands of lives in jeopardy. Thanks to the WHO's support, most of the world's countries have mobilised and implemented an 'Action Plan for Pandemic Influenza'. As a result, most outbreaks of the H5N1 avian flu virus have so far been speedily contained. Cases of dengue virus introduction in countries possessing every circumstance required for its epidemic spread provide another example pertinent to the prevention of epidemics caused by vector-borne pathogens.

Epidemic contact tracing via communication traces.

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Katayoun Farrahi

Full Text Available Traditional contact tracing relies on knowledge of the interpersonal network of physical interactions, where contagious outbreaks propagate. However, due to privacy constraints and noisy data assimilation, this network is generally difficult to reconstruct accurately. Communication traces obtained by mobile phones are known to be good proxies for the physical interaction network, and they may provide a valuable tool for contact tracing. Motivated by this assumption, we propose a model for contact tracing, where an infection is spreading in the physical interpersonal network, which can never be fully recovered; and contact tracing is occurring in a communication network which acts as a proxy for the first. We apply this dual model to a dataset covering 72 students over a 9 month period, for which both the physical interactions as well as the mobile communication traces are known. Our results suggest that a wide range of contact tracing strategies may significantly reduce the final size of the epidemic, by mainly affecting its peak of incidence. However, we find that for low overlap between the face-to-face and communication interaction network, contact tracing is only efficient at the beginning of the outbreak, due to rapidly increasing costs as the epidemic evolves. Overall, contact tracing via mobile phone communication traces may be a viable option to arrest contagious outbreaks.

Epidemic contact tracing via communication traces.

Science.gov (United States)

Farrahi, Katayoun; Emonet, Rémi; Cebrian, Manuel

2014-01-01

Traditional contact tracing relies on knowledge of the interpersonal network of physical interactions, where contagious outbreaks propagate. However, due to privacy constraints and noisy data assimilation, this network is generally difficult to reconstruct accurately. Communication traces obtained by mobile phones are known to be good proxies for the physical interaction network, and they may provide a valuable tool for contact tracing. Motivated by this assumption, we propose a model for contact tracing, where an infection is spreading in the physical interpersonal network, which can never be fully recovered; and contact tracing is occurring in a communication network which acts as a proxy for the first. We apply this dual model to a dataset covering 72 students over a 9 month period, for which both the physical interactions as well as the mobile communication traces are known. Our results suggest that a wide range of contact tracing strategies may significantly reduce the final size of the epidemic, by mainly affecting its peak of incidence. However, we find that for low overlap between the face-to-face and communication interaction network, contact tracing is only efficient at the beginning of the outbreak, due to rapidly increasing costs as the epidemic evolves. Overall, contact tracing via mobile phone communication traces may be a viable option to arrest contagious outbreaks.

Protection motivation theory and social distancing behaviour in response to a simulated infectious disease epidemic.

Science.gov (United States)

Williams, Lynn; Rasmussen, Susan; Kleczkowski, Adam; Maharaj, Savi; Cairns, Nicole

2015-01-01

Epidemics of respiratory infectious disease remain one of the most serious health risks facing the population. Non-pharmaceutical interventions (e.g. hand-washing or wearing face masks) can have a significant impact on the course of an infectious disease epidemic. The current study investigated whether protection motivation theory (PMT) is a useful framework for understanding social distancing behaviour (i.e. the tendency to reduce social contacts) in response to a simulated infectious disease epidemic. There were 230 participants (109 males, 121 females, mean age 32.4 years) from the general population who completed self-report measures assessing the components of PMT. In addition, participants completed a computer game which simulated an infectious disease epidemic in order to provide a measure of social distancing behaviour. The regression analyses revealed that none of the PMT variables were significant predictors of social distancing behaviour during the simulation task. However, fear (β = .218, p < .001), response efficacy (β = .175, p < .01) and self-efficacy (β = .251, p < .001) were all significant predictors of intention to engage in social distancing behaviour. Overall, the PMT variables (and demographic factors) explain 21.2% of the variance in intention. The findings demonstrated that PMT was a useful framework for understanding intention to engage in social distancing behaviour, but not actual behaviour during the simulated epidemic. These findings may reflect an intention-behaviour gap in relation to social distancing behaviour.

Simulation and Statistical Inference of Stochastic Reaction Networks with Applications to Epidemic Models

KAUST Repository

Moraes, Alvaro

2015-01-01

Epidemics have shaped, sometimes more than wars and natural disasters, demo- graphic aspects of human populations around the world, their health habits and their economies. Ebola and the Middle East Respiratory Syndrome (MERS) are clear and current examples of potential hazards at planetary scale. During the spread of an epidemic disease, there are phenomena, like the sudden extinction of the epidemic, that can not be captured by deterministic models. As a consequence, stochastic models have been proposed during the last decades. A typical forward problem in the stochastic setting could be the approximation of the expected number of infected individuals found in one month from now. On the other hand, a typical inverse problem could be, given a discretely observed set of epidemiological data, infer the transmission rate of the epidemic or its basic reproduction number. Markovian epidemic models are stochastic models belonging to a wide class of pure jump processes known as Stochastic Reaction Networks (SRNs), that are intended to describe the time evolution of interacting particle systems where one particle interacts with the others through a finite set of reaction channels. SRNs have been mainly developed to model biochemical reactions but they also have applications in neural networks, virus kinetics, and dynamics of social networks, among others. 4 This PhD thesis is focused on novel fast simulation algorithms and statistical inference methods for SRNs. Our novel Multi-level Monte Carlo (MLMC) hybrid simulation algorithms provide accurate estimates of expected values of a given observable of SRNs at a prescribed final time. They are designed to control the global approximation error up to a user-selected accuracy and up to a certain confidence level, and with near optimal computational work. We also present novel dual-weighted residual expansions for fast estimation of weak and strong errors arising from the MLMC methodology. Regarding the statistical inference

HIV epidemic appraisals for assisting in the design of effective prevention programmes: shifting the paradigm back to basics.

Directory of Open Access Journals (Sweden)

Sharmistha Mishra

Full Text Available To design HIV prevention programmes, it is critical to understand the temporal and geographic aspects of the local epidemic and to address the key behaviours that drive HIV transmission. Two methods have been developed to appraise HIV epidemics and guide prevention strategies. The numerical proxy method classifies epidemics based on current HIV prevalence thresholds. The Modes of Transmission (MOT model estimates the distribution of incidence over one year among risk-groups. Both methods focus on the current state of an epidemic and provide short-term metrics which may not capture the epidemiologic drivers. Through a detailed analysis of country and sub-national data, we explore the limitations of the two traditional methods and propose an alternative approach.We compared outputs of the traditional methods in five countries for which results were published, and applied the numeric and MOT model to India and six districts within India. We discovered three limitations of the current methods for epidemic appraisal: (1 their results failed to identify the key behaviours that drive the epidemic; (2 they were difficult to apply to local epidemics with heterogeneity across district-level administrative units; and (3 the MOT model was highly sensitive to input parameters, many of which required extraction from non-regional sources. We developed an alternative decision-tree framework for HIV epidemic appraisals, based on a qualitative understanding of epidemiologic drivers, and demonstrated its applicability in India. The alternative framework offered a logical algorithm to characterize epidemics; it required minimal but key data.Traditional appraisals that utilize the distribution of prevalent and incident HIV infections in the short-term could misguide prevention priorities and potentially impede efforts to halt the trajectory of the HIV epidemic. An approach that characterizes local transmission dynamics provides a potentially more effective tool with

Epidemic threshold in directed networks

Science.gov (United States)

Li, Cong; Wang, Huijuan; Van Mieghem, Piet

2013-12-01

Epidemics have so far been mostly studied in undirected networks. However, many real-world networks, such as the online social network Twitter and the world wide web, on which information, emotion, or malware spreads, are directed networks, composed of both unidirectional links and bidirectional links. We define the directionality ξ as the percentage of unidirectional links. The epidemic threshold τc for the susceptible-infected-susceptible (SIS) epidemic is lower bounded by 1/λ1 in directed networks, where λ1, also called the spectral radius, is the largest eigenvalue of the adjacency matrix. In this work, we propose two algorithms to generate directed networks with a given directionality ξ. The effect of ξ on the spectral radius λ1, principal eigenvector x1, spectral gap (λ1-λ2), and algebraic connectivity μN-1 is studied. Important findings are that the spectral radius λ1 decreases with the directionality ξ, whereas the spectral gap and the algebraic connectivity increase with the directionality ξ. The extent of the decrease of the spectral radius depends on both the degree distribution and the degree-degree correlation ρD. Hence, in directed networks, the epidemic threshold is larger and a random walk converges to its steady state faster than that in undirected networks with the same degree distribution.

Controlling nosocomial infection based on structure of hospital social networks.

Science.gov (United States)

Ueno, Taro; Masuda, Naoki

2008-10-07

Nosocomial infection (i.e. infection in healthcare facilities) raises a serious public health problem, as implied by the existence of pathogens characteristic to healthcare facilities such as methicillin-resistant Staphylococcus aureus and hospital-mediated outbreaks of influenza and severe acute respiratory syndrome. For general communities, epidemic modeling based on social networks is being recognized as a useful tool. However, disease propagation may occur in a healthcare facility in a manner different from that in a urban community setting due to different network architecture. We simulate stochastic susceptible-infected-recovered dynamics on social networks, which are based on observations in a hospital in Tokyo, to explore effective containment strategies against nosocomial infection. The observed social networks in the hospital have hierarchical and modular structure in which dense substructure such as departments, wards, and rooms, are globally but only loosely connected, and do not reveal extremely right-skewed distributions of the number of contacts per individual. We show that healthcare workers, particularly medical doctors, are main vectors (i.e. transmitters) of diseases on these networks. Intervention methods that restrict interaction between medical doctors and their visits to different wards shrink the final epidemic size more than intervention methods that directly protect patients, such as isolating patients in single rooms. By the same token, vaccinating doctors with priority rather than patients or nurses is more effective. Finally, vaccinating individuals with large betweenness centrality (frequency of mediating connection between pairs of individuals along the shortest paths) is superior to vaccinating ones with large connectedness to others or randomly chosen individuals, which was suggested by previous model studies.

Cooperative epidemics on multiplex networks

Science.gov (United States)

Azimi-Tafreshi, N.

2016-04-01

The spread of one disease, in some cases, can stimulate the spreading of another infectious disease. Here, we treat analytically a symmetric coinfection model for spreading of two diseases on a two-layer multiplex network. We allow layer overlapping, but we assume that each layer is random and locally loopless. Infection with one of the diseases increases the probability of getting infected with the other. Using the generating function method, we calculate exactly the fraction of individuals infected with both diseases (so-called coinfected clusters) in the stationary state, as well as the epidemic spreading thresholds and the phase diagram of the model. With increasing cooperation, we observe a tricritical point and the type of transition changes from continuous to hybrid. Finally, we compare the coinfected clusters in the case of cooperating diseases with the so-called "viable" clusters in networks with dependencies.

49 CFR 213.305 - Designation of qualified individuals; general qualifications.

Science.gov (United States)

2010-10-01

... college level engineering program, supplemented by special on the job training emphasizing the techniques... engineering program, supplemented by special on the job training emphasizing the techniques to be employed in... 49 Transportation 4 2010-10-01 2010-10-01 false Designation of qualified individuals; general...

Epidemic Network Failures in Optical Transport Networks

DEFF Research Database (Denmark)

Ruepp, Sarah Renée; Katsikas, Dimitrios; Fagertun, Anna Manolova

2013-01-01

This paper presents a failure propagation model for transport networks which are affected by epidemic failures. The network is controlled using the GMPLS protocol suite. The Susceptible Infected Disabled (SID) epidemic model is investigated and new signaling functionality of GMPLS to support...

[DETERMINATION OF TYPES OF EPIDEMIC MANIFESTATIONS OF CHOLERA IN REGIONS OF THE CRIMEA FEDERAL DISTRICT (REPUBLIC OF CRIMEA)].

Science.gov (United States)

Onischenko, G G; Popova, A Yu; Moskvitina, E A; Penkovskaya, N A; Listopad, S A; Titova, S V; Kruglikov, V D

2015-01-01

The aim of the study was determination of the type of epidemic manifestations of cholera in the Republic of Crimea based on evaluation of epidemic manifestations of cholera risk of introduction and spread of the infection. It was concluded, that, based on the cholera outbreaks, that had taken place, contamination of surface water bodies (fresh and sea) and sewage by Vibrio cholerae O1 ctxA+ and Vibrio cholerae O1 ctXA- potential epidemic danger of introduction of the infection by various types of international transport, population migration, the presence of epidemiologic risk in realization of water pathway of transmission of cholera causative agent and several other social conditions, the Republic of Crimea remains in the group of territories of type I by epidemic manifestations of cholera.

The smoking epidemic in Switzerland--an empirical examination of the theory of diffusion of innovations.

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Kuntsche, Sandra; Gmel, Gerhard

2005-01-01

Cultural and sex differences in smoking rates among countries indicate different phases of the smoking epidemic. Their background is summarized in a four-stage model based on the Rogers Theory of Diffusion of Innovations. First, to test predictions of the Rogers theory and, second, to test whether, according to the theory, today's innovative process is smoking cessation, predicted by higher rates of cessation among the more highly educated and among men of all educational levels. Data covered respondents older than 24 years from two Swiss Health Surveys (1997 and 2002). Logistic regression models were on lifetime smoking versus never-smoking, and on former smoking versus current smoking. Declining smoking rates in both sexes over time, measured by birth cohorts, indicate that the epidemic has peaked, but women of all educational levels and men of lower education still show high prevalence rates. The gap between higher-educated and lower-educated individuals is widening. Smoking prevalence is expected to decline further, particularly among women and little educated men. The incidence of tobacco-related diseases in women is predicted to exceed that of men, owing to their lower cessation rates.

Chaos induced by breakup of waves in a spatial epidemic model with nonlinear incidence rate

International Nuclear Information System (INIS)

Sun, Gui-Quan; Jin, Zhen; Liu, Quan-Xing; Li, Li

2008-01-01

Spatial epidemiology is the study of spatial variation in disease risk or incidence, including the spatial patterns of the population. The spread of diseases in human populations can exhibit large scale patterns, underlining the need for spatially explicit approaches. In this paper, the spatiotemporal complexity of a spatial epidemic model with nonlinear incidence rate, which includes the behavioral changes and crowding effect of the infective individuals, is investigated. Based on both theoretical analysis and computer simulations, we find out when, under the parameters which can guarantee a stable limit cycle in the non-spatial model, spiral and target waves can emerge. Moreover, two different kinds of breakup of waves are shown. Specifically, the breakup of spiral waves is from the core and the breakup of target waves is from the far-field, and both kinds of waves become irregular patterns at last. Our results reveal that the spatiotemporal chaos is induced by the breakup of waves. The results obtained confirm that diffusion can form spiral waves, target waves or spatial chaos of high population density, which enrich the findings of spatiotemporal dynamics in the epidemic model

Temporal prediction of epidemic patterns in community networks

International Nuclear Information System (INIS)

Peng, Xiao-Long; Xu, Xin-Jian; Fu, Xinchu; Small, Michael

2013-01-01

Most previous studies of epidemic dynamics on complex networks suppose that the disease will eventually stabilize at either a disease-free state or an endemic one. In reality, however, some epidemics always exhibit sporadic and recurrent behaviour in one region because of the invasion from an endemic population elsewhere. In this paper we address this issue and study a susceptible–infected–susceptible epidemiological model on a network consisting of two communities, where the disease is endemic in one community but alternates between outbreaks and extinctions in the other. We provide a detailed characterization of the temporal dynamics of epidemic patterns in the latter community. In particular, we investigate the time duration of both outbreak and extinction, and the time interval between two consecutive inter-community infections, as well as their frequency distributions. Based on the mean-field theory, we theoretically analyse these three timescales and their dependence on the average node degree of each community, the transmission parameters and the number of inter-community links, which are in good agreement with simulations, except when the probability of overlaps between successive outbreaks is too large. These findings aid us in better understanding the bursty nature of disease spreading in a local community, and thereby suggesting effective time-dependent control strategies. (paper)

Stochastic analysis of epidemics on adaptive time varying networks

Science.gov (United States)

Kotnis, Bhushan; Kuri, Joy

2013-06-01

Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

Rainfall-driven epidemic cholera: hydrologic controls on water-borne disease and multi-season projections

Science.gov (United States)

Righetto, L.; Bertuzzo, E.; Mari, L.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

2012-12-01

Following the acknowledgement of a clear correlation between rainfall events and cholera resurgence, that was observed in Haiti starting from May 2011, we use a multi-variate Poisson generator to produce rainfall inputs, with which we force spatially explicit models of cholera spreading. Our models consist of ODE systems of equations, describing a network of human communities (divided in Susceptible, Infected and Recovered individuals) connected by river transport of pathogens and human mobility. We perform an a posteriori analysis -- from the beginning of the epidemic until December 2011 -- to assess the model reliability in predicting cholera cases and in testing control measures -- involving vaccination and sanitation campaigns. We then run a multi-seasonal prediction of the course of the epidemic until December 2015, to investigate further resurgences of cholera in the region and to evaluate, again, the effect of policies which may bring to the eradication of the disease in Haiti. We conclude that mathematical models may represent a key information tool for policy makers, as a way to preliminarly assess the possible future course of an epidemic and to test intervention policies to be deployed. Effect of intervention policies on the predicted course of the epidemic between 28/05-31/12/2011 (blue lines: simulations with the observed rainfall pattern; red lines/shaded range: median/25th-75th percentile range of simulations with generated rainfall). A) Effect of a reduction of the 20% of the contact rate , applied in one month starting from the 1st of June (dashed blue/red lines) or the 1st of July (dotted blue/red lines). B) A) Effect of a vaccination of 4 million individuals, implemented in one month starting from the 1st of June (dashed blue/red lines) or the 1st of July (dotted blue/red lines). C) Number of new cases in the period 28/05-31/12/2011 as a function of the reduction of the contact rate . D) Number of new cases in the period 28/05-31/12/2011 as a

Effects of local and global network connectivity on synergistic epidemics

Science.gov (United States)

Broder-Rodgers, David; Pérez-Reche, Francisco J.; Taraskin, Sergei N.

2015-12-01

Epidemics in networks can be affected by cooperation in transmission of infection and also connectivity between nodes. An interplay between these two properties and their influence on epidemic spread are addressed in the paper. A particular type of cooperative effects (called synergy effects) is considered, where the transmission rate between a pair of nodes depends on the number of infected neighbors. The connectivity effects are studied by constructing networks of different topology, starting with lattices with only local connectivity and then with networks that have both local and global connectivity obtained by random bond-rewiring to nodes within a certain distance. The susceptible-infected-removed epidemics were found to exhibit several interesting effects: (i) for epidemics with strong constructive synergy spreading in networks with high local connectivity, the bond rewiring has a negative role in epidemic spread, i.e., it reduces invasion probability; (ii) in contrast, for epidemics with destructive or weak constructive synergy spreading on networks of arbitrary local connectivity, rewiring helps epidemics to spread; (iii) and, finally, rewiring always enhances the spread of epidemics, independent of synergy, if the local connectivity is low.

HIV among gay and other men who have sex with men in Latin America and the Caribbean: a hidden epidemic?

Science.gov (United States)

Cáceres, Carlos F

2002-12-01

To assess the epidemiological and social/cultural context of, and the social response to, the HIV epidemic among gay and other men who have sex with men (MSM) in Latin America and the Caribbean. A review of epidemiological surveillance reports to the Pan American Health Organization/UNAIDS; published studies on HIV prevalence/incidence among MSM in the region; social/cultural studies on homosexuality; documents analysing risk and vulnerability among MSM and publications documenting the social response to the MSM epidemic. The regional HIV epidemic is concentrated in MSM populations in most urban centres (HIV prevalence 5-20%). Incidence rates (1.5-3.3 in Brazil and Peru) are still moderately high, and call for continued programmatic action. Transmission from bisexual men to women is increasingly observed, demonstrating that the neglect of intervention will fuel co-existent epidemics. MSM in the region are culturally diverse, with mediation of social class, sex, and ethnicity. Around core gay subcultures, non-gay identified MSM interact with them and frequently exchange sex for goods. Examples are shown of sexual meanings affecting prevention messages focused on individual risk, as well as of the role of structural vulnerability on potential exposure to infection, calling for programmes beyond individual rational decision-making. The social response to the AIDS epidemic has, in most countries, included programmes oriented to MSM, usually from civil society organizations, and has strengthened gay organizing. Renewed, imaginative efforts are needed from governments and community organizations to strengthen culturally sensitive prevention work, and integrate it into community empowerment and the promotion of sexual rights.

Threshold-based epidemic dynamics in systems with memory

Science.gov (United States)

Bodych, Marcin; Ganguly, Niloy; Krueger, Tyll; Mukherjee, Animesh; Siegmund-Schultze, Rainer; Sikdar, Sandipan

2016-11-01

In this article we analyze an epidemic dynamics model (SI) where we assume that there are k susceptible states, that is a node would require multiple (k) contacts before it gets infected. In specific, we provide a theoretical framework for studying diffusion rate in complete graphs and d-regular trees with extensions to dense random graphs. We observe that irrespective of the topology, the diffusion process could be divided into two distinct phases: i) the initial phase, where the diffusion process is slow, followed by ii) the residual phase where the diffusion rate increases manifold. In fact, the initial phase acts as an indicator for the total diffusion time in dense graphs. The most remarkable lesson from this investigation is that such a diffusion process could be controlled and even contained if acted upon within its initial phase.

Percolation and epidemics in random clustered networks

Science.gov (United States)

Miller, Joel C.

2009-08-01

The social networks that infectious diseases spread along are typically clustered. Because of the close relation between percolation and epidemic spread, the behavior of percolation in such networks gives insight into infectious disease dynamics. A number of authors have studied percolation or epidemics in clustered networks, but the networks often contain preferential contacts in high degree nodes. We introduce a class of random clustered networks and a class of random unclustered networks with the same preferential mixing. Percolation in the clustered networks reduces the component sizes and increases the epidemic threshold compared to the unclustered networks.

Predicting extinction rates in stochastic epidemic models

International Nuclear Information System (INIS)

Schwartz, Ira B; Billings, Lora; Dykman, Mark; Landsman, Alexandra

2009-01-01

We investigate the stochastic extinction processes in a class of epidemic models. Motivated by the process of natural disease extinction in epidemics, we examine the rate of extinction as a function of disease spread. We show that the effective entropic barrier for extinction in a susceptible–infected–susceptible epidemic model displays scaling with the distance to the bifurcation point, with an unusual critical exponent. We make a direct comparison between predictions and numerical simulations. We also consider the effect of non-Gaussian vaccine schedules, and show numerically how the extinction process may be enhanced when the vaccine schedules are Poisson distributed

Computational modeling and statistical analyses on individual contact rate and exposure to disease in complex and confined transportation hubs

Science.gov (United States)

Wang, W. L.; Tsui, K. L.; Lo, S. M.; Liu, S. B.

2018-01-01

Crowded transportation hubs such as metro stations are thought as ideal places for the development and spread of epidemics. However, for the special features of complex spatial layout, confined environment with a large number of highly mobile individuals, it is difficult to quantify human contacts in such environments, wherein disease spreading dynamics were less explored in the previous studies. Due to the heterogeneity and dynamic nature of human interactions, increasing studies proved the importance of contact distance and length of contact in transmission probabilities. In this study, we show how detailed information on contact and exposure patterns can be obtained by statistical analyses on microscopic crowd simulation data. To be specific, a pedestrian simulation model-CityFlow was employed to reproduce individuals' movements in a metro station based on site survey data, values and distributions of individual contact rate and exposure in different simulation cases were obtained and analyzed. It is interesting that Weibull distribution fitted the histogram values of individual-based exposure in each case very well. Moreover, we found both individual contact rate and exposure had linear relationship with the average crowd densities of the environments. The results obtained in this paper can provide reference to epidemic study in complex and confined transportation hubs and refine the existing disease spreading models.

Beyond fast food and slow motion: weighty contributors to the obesity epidemic.

Science.gov (United States)

Cizza, G; Rother, K I

2012-02-01

Decreased physical activity and marketing-driven increased consumption of "junk" food, dubbed "The Big Two", are generally regarded as the most important contributors to the obesity epidemic. However, the full picture contains many more pieces of the puzzle. We address several additional issues and review current clinical developments in obesity research. In spite of dramatic advancements in our understanding of the adipose organ and its endocrine and immune products, the ultimate causes of the obesity epidemic remain elusive. Treatment is plagued by poor adherence to life style modifications, and available pharmacological options are marginally effective, often also associated with major side effects. Surgical treatments, albeit effective in decreasing body weight, are invasive and expensive. Thus, our approaches to finding the causes, improving the existing treatments, and inventing novel therapies must be manifold.

Suppressing traffic-driven epidemic spreading by adaptive routing strategy

International Nuclear Information System (INIS)

Yang, Han-Xin; Wang, Zhen

2016-01-01

The design of routing strategies for traffic-driven epidemic spreading has received increasing attention in recent years. In this paper, we propose an adaptive routing strategy that incorporates topological distance with local epidemic information through a tunable parameter h. In the case where the traffic is free of congestion, there exists an optimal value of routing parameter h, leading to the maximal epidemic threshold. This means that epidemic spreading can be more effectively controlled by adaptive routing, compared to that of the static shortest path routing scheme. Besides, we find that the optimal value of h can greatly relieve the traffic congestion in the case of finite node-delivering capacity. We expect our work to provide new insights into the effects of dynamic routings on traffic-driven epidemic spreading.

The severe acute respiratory syndrome epidemic in mainland China dissected.

Science.gov (United States)

Cao, Wu-Chun; de Vlas, Sake J; Richardus, Jan Hendrik

2011-03-08

This paper provides a review of a recently published series of studies that give a detailed and comprehensive documentation of the severe acute respiratory syndrome (SARS) epidemic in mainland China, which severely struck the country in the spring of 2003. The epidemic spanned a large geographical extent but clustered in two areas: first in Guangdong Province, and about 3 months later in Beijing with its surrounding areas. Reanalysis of all available epidemiological data resulted in a total of 5327 probable cases of SARS, of whom 343 died. The resulting case fatality ratio (CFR) of 6.4% was less than half of that in other SARS-affected countries or areas, and this difference could only partly be explained by younger age of patients and higher number of community acquired infections. Analysis of the impact of interventions demonstrated that strong political commitment and a centrally coordinated response was the most important factor to control SARS in mainland China, whereas the most stringent control measures were all initiated when the epidemic was already dying down. The long-term economic consequence of the epidemic was limited, much consumption was merely postponed, but for Beijing irrecoverable losses to the tourist sector were considerable. An important finding from a cohort study was that many former SARS patients currently suffer from avascular osteonecrosis, as a consequence of the treatment with corticosteroids during their infection. The SARS epidemic provided valuable information and lessons relevant in controlling outbreaks of newly emerging infectious diseases, and has led to fundamental reforms of the Chinese health system. In particular, a comprehensive nationwide internet-based disease reporting system was established.

The severe acute respiratory syndrome epidemic in mainland China dissected

Directory of Open Access Journals (Sweden)

Wuchun Cao

2011-02-01

Full Text Available This paper provides a review of a recently published series of studies that give a detailed and comprehensive documentation of the severe acute respiratory syndrome (SARS epidemic in mainland China, which severely struck the country in the spring of 2003. The epidemic spanned a large geographical extent but clustered in two areas: first in Guangdong Province, and about 3 months later in Beijing with its surrounding areas. Reanalysis of all available epidemiological data resulted in a total of 5327 probable cases of SARS, of whom 343 died. The resulting case fatality ratio (CFR of 6.4% was less than half of that in other SARS-affected countries or areas, and this difference could only partly be explained by younger age of patients and higher number of community acquired infections. Analysis of the impact of interventions demonstrated that strong political commitment and a centrally coordinated response was the most important factor to control SARS in mainland China, whereas the most stringent control measures were all initiated when the epidemic was already dying down. The long-term economic consequence of the epidemic was limited, much consumption was merely postponed, but for Beijing irrecoverable losses to the tourist sector were considerable. An important finding from a cohort study was that many former SARS patients currently suffer from avascular osteo­necrosis, as a consequence of the treatment with corticosteroids during their infection. The SARS epidemic provided valuable information and lessons relevant in controlling outbreaks of newly emerging infectious diseases, and has led to fundamental reforms of the Chinese health system. In particular, a comprehensive nation-wide internet-based disease reporting system was established.

Suppressing epidemics with a limited amount of immunization units.

Science.gov (United States)

Schneider, Christian M; Mihaljev, Tamara; Havlin, Shlomo; Herrmann, Hans J

2011-12-01

The way diseases spread through schools, epidemics through countries, and viruses through the internet is crucial in determining their risk. Although each of these threats has its own characteristics, its underlying network determines the spreading. To restrain the spreading, a widely used approach is the fragmentation of these networks through immunization, so that epidemics cannot spread. Here we develop an immunization approach based on optimizing the susceptible size, which outperforms the best known strategy based on immunizing the highest-betweenness links or nodes. We find that the network's vulnerability can be significantly reduced, demonstrating this on three different real networks: the global flight network, a school friendship network, and the internet. In all cases, we find that not only is the average infection probability significantly suppressed, but also for the most relevant case of a small and limited number of immunization units the infection probability can be reduced by up to 55%.

Modelling control of epidemics spreading by long-range interactions.

Science.gov (United States)

Dybiec, Bartłomiej; Kleczkowski, Adam; Gilligan, Christopher A

2009-10-06

We have studied the spread of epidemics characterized by a mixture of local and non-local interactions. The infection spreads on a two-dimensional lattice with the fixed nearest neighbour connections. In addition, long-range dynamical links are formed by moving agents (vectors). Vectors perform random walks, with step length distributed according to a thick-tail distribution. Two distributions are considered in this paper, an alpha-stable distribution describing self-similar vector movement, yet characterized by an infinite variance and an exponential power characterized by a large but finite variance. Such long-range interactions are hard to track and make control of epidemics very difficult. We also allowed for cryptic infection, whereby an infected individual on the lattice can be infectious prior to showing any symptoms of infection or disease. To account for such cryptic spread, we considered a control strategy in which not only detected, i.e. symptomatic, individuals but also all individuals within a certain control neighbourhood are treated upon the detection of disease. We show that it is possible to eradicate the disease by using such purely local control measures, even in the presence of long-range jumps. In particular, we show that the success of local control and the choice of the optimal strategy depend in a non-trivial way on the dispersal patterns of the vectors. By characterizing these patterns using the stability index of the alpha-stable distribution to change the power-law behaviour or the exponent characterizing the decay of an exponential power distribution, we show that infection can be successfully contained using relatively small control neighbourhoods for two limiting cases for long-distance dispersal and for vectors that are much more limited in their dispersal range.

Epidemic dynamics and endemic states in complex networks

OpenAIRE

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2001-01-01

We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below which the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are pron...

Implementation and validation of an economic module in the Be-FAST model to predict costs generated by livestock disease epidemics: Application to classical swine fever epidemics in Spain.

Science.gov (United States)

Fernández-Carrión, E; Ivorra, B; Martínez-López, B; Ramos, A M; Sánchez-Vizcaíno, J M

2016-04-01

Be-FAST is a computer program based on a time-spatial stochastic spread mathematical model for studying the transmission of infectious livestock diseases within and between farms. The present work describes a new module integrated into Be-FAST to model the economic consequences of the spreading of classical swine fever (CSF) and other infectious livestock diseases within and between farms. CSF is financially one of the most damaging diseases in the swine industry worldwide. Specifically in Spain, the economic costs in the two last CSF epidemics (1997 and 2001) reached jointly more than 108 million euros. The present analysis suggests that severe CSF epidemics are associated with significant economic costs, approximately 80% of which are related to animal culling. Direct costs associated with control measures are strongly associated with the number of infected farms, while indirect costs are more strongly associated with epidemic duration. The economic model has been validated with economic information around the last outbreaks in Spain. These results suggest that our economic module may be useful for analysing and predicting economic consequences of livestock disease epidemics. Copyright © 2016 Elsevier B.V. All rights reserved.

Topographic determinants of foot and mouth disease transmission in the UK 2001 epidemic

Directory of Open Access Journals (Sweden)

Keeling Matthew J

2006-01-01

Full Text Available Abstract Background A key challenge for modelling infectious disease dynamics is to understand the spatial spread of infection in real landscapes. This ideally requires a parallel record of spatial epidemic spread and a detailed map of susceptible host density along with relevant transport links and geographical features. Results Here we analyse the most detailed such data to date arising from the UK 2001 foot and mouth epidemic. We show that Euclidean distance between infectious and susceptible premises is a better predictor of transmission risk than shortest and quickest routes via road, except where major geographical features intervene. Conclusion Thus, a simple spatial transmission kernel based on Euclidean distance suffices in most regions, probably reflecting the multiplicity of transmission routes during the epidemic.

Zika virus epidemic in Puerto Rico: Health justice too long delayed

Directory of Open Access Journals (Sweden)

Carlos E. Rodríguez-Díaz

2017-12-01

Full Text Available Over the course of 16 months, more than 35 400 cases of Zika virus infection have been confirmed in Puerto Rico. This represents 85% of all cases reported in the USA and its territories. The Zika epidemic is exposing the profound failure of socioeconomic policies, as well as the failure to protect sexual and reproductive health rights in Puerto Rico. Considering the high poverty rates, high levels of sexuality-related stigma, poor quality sex education, limited access to contraception, and limited participation in the allocation of resources for prevention, it is unreasonable to focus public health efforts to prevent Zika virus infection on vector control. The allocation and equitable management of resources for research and intervention are required in order to understand and address the barriers to and facilitators of prevention at the individual, social, and structural levels. Further, the impact of efforts to tackle the social determinants of the Zika virus epidemic on the island should be assessed.

Stemming the obesity epidemic : a tantalizing prospect

NARCIS (Netherlands)

Veerman, J Lennert; Barendregt, Jan J; van Beeck, Ed F; Seidell, Jacob C; Mackenbach, Johan P

OBJECTIVE: Obesity is a growing problem worldwide, but there are no good methods to assess the future course of the epidemic and the potential influence of interventions. We explore the behavior change needed to stop the obesity epidemic in the U.S. RESEARCH METHODS AND PROCEDURES: We modeled the

The evolutionary rate dynamically tracks changes in HIV-1 epidemics

Energy Technology Data Exchange (ETDEWEB)

Maljkovic-berry, Irina [Los Alamos National Laboratory; Athreya, Gayathri [Los Alamos National Laboratory; Daniels, Marcus [Los Alamos National Laboratory; Bruno, William [Los Alamos National Laboratory; Korber, Bette [Los Alamos National Laboratory; Kuiken, Carla [Los Alamos National Laboratory; Ribeiro, Ruy M [Los Alamos National Laboratory

2009-01-01

Large-sequence datasets provide an opportunity to investigate the dynamics of pathogen epidemics. Thus, a fast method to estimate the evolutionary rate from large and numerous phylogenetic trees becomes necessary. Based on minimizing tip height variances, we optimize the root in a given phylogenetic tree to estimate the most homogenous evolutionary rate between samples from at least two different time points. Simulations showed that the method had no bias in the estimation of evolutionary rates and that it was robust to tree rooting and topological errors. We show that the evolutionary rates of HIV-1 subtype B and C epidemics have changed over time, with the rate of evolution inversely correlated to the rate of virus spread. For subtype B, the evolutionary rate slowed down and tracked the start of the HAART era in 1996. Subtype C in Ethiopia showed an increase in the evolutionary rate when the prevalence increase markedly slowed down in 1995. Thus, we show that the evolutionary rate of HIV-1 on the population level dynamically tracks epidemic events.

Could the Recent Zika Epidemic Have Been Predicted?

Science.gov (United States)

Vecchi, G. A.; Munoz, A. G.; Thomson, M. C.; Stewart-Ibarra, A. M.; Chourio, X.; Nájera, P.; Moran, Z.; Yang, X.

2017-12-01

Given knowledge at the time, the recent 2015-2016 zika virus (ZIKV) epidemic probably could not have been predicted. Without the prior knowledge of ZIKV being already present in South America, and given the lack of understanding of key epidemiologic processes and long-term records of ZIKV cases in the continent, the best related prediction could be carried out for the potential risk of a generic Aedes-borne disease epidemic. Here we use a recently published two-vector basic reproduction number model to assess the predictability of the conditions conducive to epidemics of diseases like zika, chikungunya, or dengue, transmitted by the independent or concurrent presence of Aedes aegypti and Aedes albopictus. We compare the potential risk of transmission forcing the model with the observed climate and with state-of-the-art operational forecasts from the North American Multi Model Ensemble (NMME), finding that the predictive skill of this new seasonal forecast system is highest for multiple countries in Latin America and the Caribbean during the December-February and March-May seasons, and slightly lower—but still of potential use to decision-makers—for the rest of the year. In particular, we find that above-normal suitable conditions for the occurrence of the zika epidemic at the beginning of 2015 could have been successfully predicted at least 1 month in advance for several zika hotspots, and in particular for Northeast Brazil: the heart of the epidemic. Nonetheless, the initiation and spread of an epidemic depends on the effect of multiple factors beyond climate conditions, and thus this type of approach must be considered as a guide and not as a formal predictive tool of vector-borne epidemics.

The final size of an epidemic and its relation to the basic reproduction number

DEFF Research Database (Denmark)

Andreasen, Viggo

2011-01-01

We study the final size equation for an epidemic in a subdivided population with general mixing patterns among subgroups. The equation is determined by a matrix with the same spectrum as the next generation matrix and it exhibits a threshold controlled by the common dominant eigenvalue, the basic...

Rapid simulation of spatial epidemics: a spectral method.

Science.gov (United States)

Brand, Samuel P C; Tildesley, Michael J; Keeling, Matthew J

2015-04-07

Spatial structure and hence the spatial position of host populations plays a vital role in the spread of infection. In the majority of situations, it is only possible to predict the spatial spread of infection using simulation models, which can be computationally demanding especially for large population sizes. Here we develop an approximation method that vastly reduces this computational burden. We assume that the transmission rates between individuals or sub-populations are determined by a spatial transmission kernel. This kernel is assumed to be isotropic, such that the transmission rate is simply a function of the distance between susceptible and infectious individuals; as such this provides the ideal mechanism for modelling localised transmission in a spatial environment. We show that the spatial force of infection acting on all susceptibles can be represented as a spatial convolution between the transmission kernel and a spatially extended 'image' of the infection state. This representation allows the rapid calculation of stochastic rates of infection using fast-Fourier transform (FFT) routines, which greatly improves the computational efficiency of spatial simulations. We demonstrate the efficiency and accuracy of this fast spectral rate recalculation (FSR) method with two examples: an idealised scenario simulating an SIR-type epidemic outbreak amongst N habitats distributed across a two-dimensional plane; the spread of infection between US cattle farms, illustrating that the FSR method makes continental-scale outbreak forecasting feasible with desktop processing power. The latter model demonstrates which areas of the US are at consistently high risk for cattle-infections, although predictions of epidemic size are highly dependent on assumptions about the tail of the transmission kernel. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Obesity Epidemic

Centers for Disease Control (CDC) Podcasts

2011-07-18

Learn about obesity and the community initiatives taking place to prevent and reduce this epidemic.  Created: 7/18/2011 by National Center for Chronic Disease Prevention and Health Promotion, Division of Nutrition, Physical Activity and Obesity.   Date Released: 7/18/2011.

Epidemic spreading with activity-driven awareness diffusion on multiplex network.

Science.gov (United States)

Guo, Quantong; Lei, Yanjun; Jiang, Xin; Ma, Yifang; Huo, Guanying; Zheng, Zhiming

2016-04-01

There has been growing interest in exploring the interplay between epidemic spreading with human response, since it is natural for people to take various measures when they become aware of epidemics. As a proper way to describe the multiple connections among people in reality, multiplex network, a set of nodes interacting through multiple sets of edges, has attracted much attention. In this paper, to explore the coupled dynamical processes, a multiplex network with two layers is built. Specifically, the information spreading layer is a time varying network generated by the activity driven model, while the contagion layer is a static network. We extend the microscopic Markov chain approach to derive the epidemic threshold of the model. Compared with extensive Monte Carlo simulations, the method shows high accuracy for the prediction of the epidemic threshold. Besides, taking different spreading models of awareness into consideration, we explored the interplay between epidemic spreading with awareness spreading. The results show that the awareness spreading can not only enhance the epidemic threshold but also reduce the prevalence of epidemics. When the spreading of awareness is defined as susceptible-infected-susceptible model, there exists a critical value where the dynamical process on the awareness layer can control the onset of epidemics; while if it is a threshold model, the epidemic threshold emerges an abrupt transition with the local awareness ratio α approximating 0.5. Moreover, we also find that temporal changes in the topology hinder the spread of awareness which directly affect the epidemic threshold, especially when the awareness layer is threshold model. Given that the threshold model is a widely used model for social contagion, this is an important and meaningful result. Our results could also lead to interesting future research about the different time-scales of structural changes in multiplex networks.

Epidemic spreading with activity-driven awareness diffusion on multiplex network

Science.gov (United States)

Guo, Quantong; Lei, Yanjun; Jiang, Xin; Ma, Yifang; Huo, Guanying; Zheng, Zhiming

2016-04-01

There has been growing interest in exploring the interplay between epidemic spreading with human response, since it is natural for people to take various measures when they become aware of epidemics. As a proper way to describe the multiple connections among people in reality, multiplex network, a set of nodes interacting through multiple sets of edges, has attracted much attention. In this paper, to explore the coupled dynamical processes, a multiplex network with two layers is built. Specifically, the information spreading layer is a time varying network generated by the activity driven model, while the contagion layer is a static network. We extend the microscopic Markov chain approach to derive the epidemic threshold of the model. Compared with extensive Monte Carlo simulations, the method shows high accuracy for the prediction of the epidemic threshold. Besides, taking different spreading models of awareness into consideration, we explored the interplay between epidemic spreading with awareness spreading. The results show that the awareness spreading can not only enhance the epidemic threshold but also reduce the prevalence of epidemics. When the spreading of awareness is defined as susceptible-infected-susceptible model, there exists a critical value where the dynamical process on the awareness layer can control the onset of epidemics; while if it is a threshold model, the epidemic threshold emerges an abrupt transition with the local awareness ratio α approximating 0.5. Moreover, we also find that temporal changes in the topology hinder the spread of awareness which directly affect the epidemic threshold, especially when the awareness layer is threshold model. Given that the threshold model is a widely used model for social contagion, this is an important and meaningful result. Our results could also lead to interesting future research about the different time-scales of structural changes in multiplex networks.

Critiquing the response to the Ebola epidemic through a Primary Health Care Approach.

Science.gov (United States)

Scott, Vera; Crawford-Browne, Sarah; Sanders, David

2016-05-17

The 2014/2015 West Africa Ebola epidemic has caused the global public health community to engage in difficult self-reflection. First, it must consider the part it played in relation to an important public health question: why did this epidemic take hold and spread in this unprecedented manner? Second, it must use the lessons learnt to answer the subsequent question: what can be done now to prevent further such outbreaks in the future? These questions remain relevant, even as scientists announce that the Guinea Phase III efficacy vaccine trial shows that rVSV-EBOV (Merck, Sharp & Dohme) is highly efficacious in individuals. This is a major breakthrough in the fight against Ebola virus disease (EVD). It does not replace but may be a powerful adjunct to current strategies of EVD management and control. We contribute to the current self-reflection by presenting an analysis using a Primary Health Care (PHC) approach. This approach is appropriate as African countries in the region affected by EVD have recommitted themselves to PHC as a framework for organising health systems and the delivery of health services. The approach suggests that, in an epidemic made complex by weak pre-existing health systems, lack of trust in authorities and mobile populations, a broader approach is required to engage affected communities. In the medium-term health system development with attention to primary level services and community-based programmes to address the major disease burden of malaria, diarrhoeal disease, meningitis, tuberculosis and malnutrition is needed. This requires the development of local management and an investment in human resources for health. Crucially this has to be developed ahead of, and not in parallel with, future outbreaks. In the longer-term a commitment is required to address the underlying social determinants which make these countries so vulnerable, and limit their capacity to respond effectively to, epidemics such as EVD. The PHC approach offers an

Critiquing the response to the Ebola epidemic through a Primary Health Care Approach

Directory of Open Access Journals (Sweden)

Vera Scott

2016-05-01

Full Text Available Abstract Background The 2014/2015 West Africa Ebola epidemic has caused the global public health community to engage in difficult self-reflection. First, it must consider the part it played in relation to an important public health question: why did this epidemic take hold and spread in this unprecedented manner? Second, it must use the lessons learnt to answer the subsequent question: what can be done now to prevent further such outbreaks in the future? These questions remain relevant, even as scientists announce that the Guinea Phase III efficacy vaccine trial shows that rVSV-EBOV (Merck, Sharp & Dohme is highly efficacious in individuals. This is a major breakthrough in the fight against Ebola virus disease (EVD. It does not replace but may be a powerful adjunct to current strategies of EVD management and control. Discussion We contribute to the current self-reflection by presenting an analysis using a Primary Health Care (PHC approach. This approach is appropriate as African countries in the region affected by EVD have recommitted themselves to PHC as a framework for organising health systems and the delivery of health services. The approach suggests that, in an epidemic made complex by weak pre-existing health systems, lack of trust in authorities and mobile populations, a broader approach is required to engage affected communities. In the medium-term health system development with attention to primary level services and community-based programmes to address the major disease burden of malaria, diarrhoeal disease, meningitis, tuberculosis and malnutrition is needed. This requires the development of local management and an investment in human resources for health. Crucially this has to be developed ahead of, and not in parallel with, future outbreaks. In the longer-term a commitment is required to address the underlying social determinants which make these countries so vulnerable, and limit their capacity to respond effectively to, epidemics

Epidemic pasteurellosis in a bighorn sheep population coinciding with the appearance of a domestic sheep.

Science.gov (United States)

George, Janet L; Martin, Daniel J; Lukacs, Paul M; Miller, Michael W

2008-04-01

A pneumonia epidemic reduced bighorn sheep (Ovis canadensis) survival and recruitment during 1997-2000 in a population comprised of three interconnected wintering herds (Kenosha Mountains, Sugarloaf Mountain, Twin Eagles) that inhabited the Kenosha and Tarryall Mountain ranges in central Colorado, USA. The onset of this epidemic coincided temporally and spatially with the appearance of a single domestic sheep (Ovis aires) on the Sugarloaf Mountain herd's winter range in December 1997. Although only bighorns in the Sugarloaf Mountain herd were affected in 1997-98, cases also occurred during 1998-99 in the other two wintering herds, likely after the epidemic spread via established seasonal movements of male bighorns. In all, we located 86 bighorn carcasses during 1997-2000. Three species of Pasteurella were isolated in various combinations from affected lung tissues from 20 bighorn carcasses where tissues were available and suitable for diagnostic evaluation; with one exception, beta-hemolytic mannheimia (Pasteurella) haemolytica (primarily reported as biogroup 1(G) or 1(alphaG)) was isolated from lung tissues of cases evaluated during winter 1997-98. The epidemic dramatically lowered adult bighorn monthly survival in all three herds; a model that included an acute epidemic effect, differing between sexes and with vaccination status, that diminished linearly over the next 12 mo best represented field data. In addition to the direct mortality associated with epidemics in these three herds, lamb recruitment in years following the pneumonia epidemic also was depressed as compared to years prior to the epidemic. Based on observations presented here, pasteurellosis epidemics in free-ranging bighorn sheep can arise through incursion of domestic sheep onto native ranges, and thus minimizing contact between domestic and bighorn sheep appears to be a logical principle for bighorn sheep conservation.

The yellow Fever epidemic in Western mali, september-november 1987: why did epidemiological surveillance fail?

Science.gov (United States)

Kurz, X

1990-03-01

Recent yellow fever epidemics in West Africa have underlined the discrepancy between the official number of cases and deaths and those estimated by a retrospective epidemiological investigation. During the yellow fever epidemic that broke out in western Mali in September 1987, a total of 305 cases and 145 deaths were officially notified, but estimates revealed true figures abut five times higher. This paper attempts to discuss the factors that hindered early case detection and more complete reporting. They were, first, the insufficient training on the clinical diagnosis, the blood sampling method for laboratory confirmation, and the curative treatment of patients (resulting in low utilization of services); second, the lack of an action plan to prepare in advance a quick response to the epidemic, affecting reporting procedures at the peripheral level and active case-finding during the outbreak; and third, the lack of laboratory facilities for a quick confirmation of the disease. The difficulties experienced during the yellow fever epidemic in Mali demonstrated the importance of a preparedness strategy for epidemic control, based on an integrated approach of epidemiological surveillance within basic health service activities. The need for regional collaboration and for institutionalized funds in the donor community that could be mobilized for epidemic preparedness activities is also emphasized.

The influence of school holiday timing on epidemic impact.

Science.gov (United States)

Eames, K T D

2014-09-01

The impact of reactive school closure on an epidemic is uncertain, since it is not clear how an unplanned closure will affect social mixing patterns. The effect of school holidays on social mixing patterns is better understood. Here, we use mathematical models to explore the influence of the timing of school holidays on the final size and peak incidence of an influenza-like epidemic. A well-timed holiday can reduce the impact of an epidemic, in particular substantially reducing an epidemic's peak. Final size and peak incidence cannot both be minimized: a later holiday is optimal for minimizing the final size, while an earlier holiday minimizes peak incidence. Using social mixing data from the UK, we estimated that, had the 2009 influenza epidemic not been interrupted by the school summer holidays, the final size would have been about 20% larger and the peak about 170% higher.

Parsing the peanut panic: the social life of a contested food allergy epidemic.

Science.gov (United States)

Waggoner, Miranda R

2013-08-01

As medical reports over the last decade indicate that food allergies among children are on the rise, peanut allergies in particular have become a topic of intense social debate. While peanut allergies are potentially fatal, they affect very few children at the population level. Yet, peanut allergies are characterized in medical and popular literature as a rising "epidemic," and myriad and broad-based social responses have emerged to address peanut allergy risk in public spaces. This analysis compares medical literature to other textual sources, including media reports, legislation, and advocacy between 1980 and 2010 in order to examine how peanut allergies transformed from a rare medical malady into a contemporary public health problem. I argue that the peanut allergy epidemic was co-constructed through interactions between experts, publics, biomedical categories, and institutions, while social reactions to the putative epidemic expanded the sphere of surveillance and awareness of peanut allergy risk. The characterization of the peanut allergy problem as an epidemic was shaped by mobility across social sites, with both discursive and material effects. Copyright © 2013 Elsevier Ltd. All rights reserved.

The narcissism epidemic is dead : Long live the narcissism epidemic

NARCIS (Netherlands)

Wetzel, Eunike; Brown, Anna; Hill, Patrick; Chung, J.M.H.; Robins, R.W.; Roberts, B.W.

2017-01-01

Are recent cohorts of college students more narcissistic than their predecessors? To address debates about the so-called “narcissism epidemic,” we used data from three cohorts of students (N1990s = 1,166; N2000s = 33,647; N2010s = 25,412) to test whether narcissism levels (overall and specific

A hidden HIV epidemic among women in Vietnam

Directory of Open Access Journals (Sweden)

Tran Hien

2008-01-01

need. Conclusion Women in Vietnam are increasingly at risk of HIV transmission but that risk is under-reported and under-recognized. The reasons are that women are not getting tested, are not aware of risks, do not protect themselves and are not being protected by men. Based on this information, policy-makers and planners can develop better prevention and care programs that not only address women's needs but also reduce further spread of the infection among the general population.

Beyond fast food and slow motion: Weighty contributors to the obesity epidemic

Science.gov (United States)

Cizza, G.; Rother, K.I.

2012-01-01

Decreased physical activity and marketing-driven increased consumption of “junk” food, dubbed “The Big Two”, are generally regarded as the most important contributors to the obesity epidemic. However, the full picture contains many more pieces of the puzzle. We address several additional issues and review current clinical developments in obesity research. In spite of dramatic advancements in our understanding of the adipose organ and its endocrine and immune products, the ultimate causes of the obesity epidemic remain elusive. Treatment is plagued by poor adherence to life style modifications, and available pharmacological options are marginally effective, often also associated with major side effects. Surgical treatments, albeit effective in decreasing body weight, are invasive and expensive. Thus, our approaches to finding the causes, improving the existing treatments, and inventing novel therapies must be manifold. PMID:22183119

Could the Recent Zika Epidemic Have Been Predicted?

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Ángel G. Muñoz

2017-07-01

Full Text Available Given knowledge at the time, the recent 2015–2016 zika virus (ZIKV epidemic probably could not have been predicted. Without the prior knowledge of ZIKV being already present in South America, and given the lack of understanding of key epidemiologic processes and long-term records of ZIKV cases in the continent, the best related prediction could be carried out for the potential risk of a generic Aedes-borne disease epidemic. Here we use a recently published two-vector basic reproduction number model to assess the predictability of the conditions conducive to epidemics of diseases like zika, chikungunya, or dengue, transmitted by the independent or concurrent presence of Aedes aegypti and Aedes albopictus. We compare the potential risk of transmission forcing the model with the observed climate and with state-of-the-art operational forecasts from the North American Multi Model Ensemble (NMME, finding that the predictive skill of this new seasonal forecast system is highest for multiple countries in Latin America and the Caribbean during the December-February and March-May seasons, and slightly lower—but still of potential use to decision-makers—for the rest of the year. In particular, we find that above-normal suitable conditions for the occurrence of the zika epidemic at the beginning of 2015 could have been successfully predicted at least 1 month in advance for several zika hotspots, and in particular for Northeast Brazil: the heart of the epidemic. Nonetheless, the initiation and spread of an epidemic depends on the effect of multiple factors beyond climate conditions, and thus this type of approach must be considered as a guide and not as a formal predictive tool of vector-borne epidemics.

FluDetWeb: an interactive web-based system for the early detection of the onset of influenza epidemics.

Science.gov (United States)

Conesa, David; López-Quílez, Antonio; Martínez-Beneito, Miguel Angel; Miralles, María Teresa; Verdejo, Francisco

2009-07-29

The early identification of influenza outbreaks has became a priority in public health practice. A large variety of statistical algorithms for the automated monitoring of influenza surveillance have been proposed, but most of them require not only a lot of computational effort but also operation of sometimes not-so-friendly software. In this paper, we introduce FluDetWeb, an implementation of a prospective influenza surveillance methodology based on a client-server architecture with a thin (web-based) client application design. Users can introduce and edit their own data consisting of a series of weekly influenza incidence rates. The system returns the probability of being in an epidemic phase (via e-mail if desired). When the probability is greater than 0.5, it also returns the probability of an increase in the incidence rate during the following week. The system also provides two complementary graphs. This system has been implemented using statistical free-software (R and WinBUGS), a web server environment for Java code (Tomcat) and a software module created by us (Rdp) responsible for managing internal tasks; the software package MySQL has been used to construct the database management system. The implementation is available on-line from: http://www.geeitema.org/meviepi/fludetweb/. The ease of use of FluDetWeb and its on-line availability can make it a valuable tool for public health practitioners who want to obtain information about the probability that their system is in an epidemic phase. Moreover, the architecture described can also be useful for developers of systems based on computationally intensive methods.

epidemic teach us?

African Journals Online (AJOL)

frequently brings shame, fear and guilt: dealing with this for some will begin a process of .... 'AZT treatment will have a limited effect on the epidemic, as we are targeting ... others to make the decisions that control my life. It is ironic that a society ...

2,500-year Evolution of the Term Epidemic

Science.gov (United States)

Martin-Granel, Estelle

2006-01-01

The term epidemic (from the Greek epi [on] plus demos [people]), first used by Homer, took its medical meaning when Hippocrates used it as the title of one of his famous treatises. At that time, epidemic was the name given to a collection of clinical syndromes, such as coughs or diarrheas, occurring and propagating in a given period at a given location. Over centuries, the form and meaning of the term have changed. Successive epidemics of plague in the Middle Ages contributed to the definition of an epidemic as the propagation of a single, well-defined disease. The meaning of the term continued to evolve in the 19th-century era of microbiology. Its most recent semantic evolution dates from the last quarter of the 20th century, and this evolution is likely to continue in the future. PMID:16707055

The epidemic of Tuberculosis on vaccinated population

Science.gov (United States)

Syahrini, Intan; Sriwahyuni; Halfiani, Vera; Meurah Yuni, Syarifah; Iskandar, Taufiq; Rasudin; Ramli, Marwan

2017-09-01

Tuberculosis is an infectious disease which has caused a large number of mortality in Indonesia. This disease is caused by Mycrobacterium tuberculosis. Besides affecting lung, this disease also affects other organs such as lymph gland, intestine, kidneys, uterus, bone, and brain. This article discusses the epidemic of tuberculosis through employing the SEIR model. Here, the population is divided into four compartments which are susceptible, exposed, infected and recovered. The susceptible population is further grouped into two which are vaccinated group and unvaccinated group. The behavior of the epidemic is investigated through analysing the equilibrium of the model. The result shows that administering vaccine to the susceptible population contributes to the reduction of the tuberculosis epidemic rate.

Epidemic spreading on interconnected networks.

Science.gov (United States)

Saumell-Mendiola, Anna; Serrano, M Ángeles; Boguñá, Marián

2012-08-01

Many real networks are not isolated from each other but form networks of networks, often interrelated in nontrivial ways. Here, we analyze an epidemic spreading process taking place on top of two interconnected complex networks. We develop a heterogeneous mean-field approach that allows us to calculate the conditions for the emergence of an endemic state. Interestingly, a global endemic state may arise in the coupled system even though the epidemics is not able to propagate on each network separately and even when the number of coupling connections is small. Our analytic results are successfully confronted against large-scale numerical simulations.

Epidemic Spread in Networks Induced by Deactivation Mechanism

International Nuclear Information System (INIS)

Yu Xiaoling; Wu Xiao; Zhang Duanming; Li Zhihao; Liang Fang; Wang Xiaoyu

2008-01-01

We have studied the topology and epidemic spreading behaviors on the networks in which deactivation mechanism and long-rang connection are coexisted. By means of numerical simulation, we find that the clustering coefficient C and the Pearson correlation coefficient r decrease with increasing long-range connection μ and the topological state of the network changes into that of BA model at the end (when μ = 1). For the Susceptible-Infect-Susceptible model of epidemics, the epidemic threshold can reach maximum value at μ = 0.4 and presents two different variable states around μ = 0.4

The need for data science in epidemic modelling. Comment on: "Mathematical models to characterize early epidemic growth: A review" by Gerardo Chowell et al.

Science.gov (United States)

Danon, Leon; Brooks-Pollock, Ellen

2016-09-01

In their review, Chowell et al. consider the ability of mathematical models to predict early epidemic growth [1]. In particular, they question the central prediction of classical differential equation models that the number of cases grows exponentially during the early stages of an epidemic. Using examples including HIV and Ebola, they argue that classical models fail to capture key qualitative features of early growth and describe a selection of models that do capture non-exponential epidemic growth. An implication of this failure is that predictions may be inaccurate and unusable, highlighting the need for care when embarking upon modelling using classical methodology. There remains a lack of understanding of the mechanisms driving many observed epidemic patterns; we argue that data science should form a fundamental component of epidemic modelling, providing a rigorous methodology for data-driven approaches, rather than trying to enforce established frameworks. The need for refinement of classical models provides a strong argument for the use of data science, to identify qualitative characteristics and pinpoint the mechanisms responsible for the observed epidemic patterns.

Dewey: A Panacea for the 'Schoolification' Epidemic

Science.gov (United States)

Ring, Emer; O'Sullivan, Lisha

2018-01-01

High quality early years' education is associated with providing a child-centred curriculum based on a knowledge of how young children learn. The global 'schoolification epidemic' has led to an increasing focus on prescribed curricula and presents as a serious threat to the quality of children's early years' experiences. Findings from research in…

Transferring the Malaria Epidemic Prediction Model to Users in East ...

International Development Research Centre (IDRC) Digital Library (Canada)

Transferring the Malaria Epidemic Prediction Model to Users in East Africa. In the highlands of East Africa, epidemic malaria is an emerging climate-related hazard that urgently needs addressing. Malaria incidence increased by 337% during the 1987 epidemic in Rwanda. In Tanzania, Uganda and Kenya, malaria incidence ...

Recent results on the spatiotemporal modelling and comparative analysis of Black Death and bubonic plague epidemics

Science.gov (United States)

Christakos, G.; Olea, R.A.; Yu, H.-L.

2007-01-01

Background: This work demonstrates the importance of spatiotemporal stochastic modelling in constructing maps of major epidemics from fragmentary information, assessing population impacts, searching for possible etiologies, and performing comparative analysis of epidemics. Methods: Based on the theory previously published by the authors and incorporating new knowledge bases, informative maps of the composite space-time distributions were generated for important characteristics of two major epidemics: Black Death (14th century Western Europe) and bubonic plague (19th-20th century Indian subcontinent). Results: The comparative spatiotemporal analysis of the epidemics led to a number of interesting findings: (1) the two epidemics exhibited certain differences in their spatiotemporal characteristics (correlation structures, trends, occurrence patterns and propagation speeds) that need to be explained by means of an interdisciplinary effort; (2) geographical epidemic indicators confirmed in a rigorous quantitative manner the partial findings of isolated reports and time series that Black Death mortality was two orders of magnitude higher than that of bubonic plague; (3) modern bubonic plague is a rural disease hitting harder the small villages in the countryside whereas Black Death was a devastating epidemic that indiscriminately attacked large urban centres and the countryside, and while the epidemic in India lasted uninterruptedly for five decades, in Western Europe it lasted three and a half years; (4) the epidemics had reverse areal extension features in response to annual seasonal variations. Temperature increase at the end of winter led to an expansion of infected geographical area for Black Death and a reduction for bubonic plague, reaching a climax at the end of spring when the infected area in Western Europe was always larger than in India. Conversely, without exception, the infected area during winter was larger for the Indian bubonic plague; (5) during the

Epidemic Intelligence. Langmuir and the Birth of Disease Surveillance

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Lyle Fearnley

2010-12-01

Full Text Available In the wake of the SARS and influenza epidemics of the past decade, one public health solution has become a refrain: surveillance systems for detection of disease outbreaks. This paper is an effort to understand how disease surveillance for outbreak detection gained such paramount rationality in contemporary public health. The epidemiologist Alexander Langmuir is well known as the creator of modern disease surveillance. But less well known is how he imagined disease surveillance as one part of what he called “epidemic intelligence.” Langmuir developed the practice of disease surveillance during an unprecedented moment in which the threat of biological warfare brought civil defense experts and epidemiologists together around a common problem. In this paper, I describe how Langmuir navigated this world, experimenting with new techniques and rationales of epidemic control. Ultimately, I argue, Langmuir′s experiments resulted in a set of techniques and infrastructures – a system of epidemic intelligence – that transformed the epidemic as an object of human art.

Hybrid epidemic spreading - from Internet worms to HIV infection

OpenAIRE

Zhang, C.

2015-01-01

Epidemic phenomena are ubiquitous, ranging from infectious diseases, computer viruses, to information dissemination. Epidemics have traditionally been studied as a single spreading process, either in a fully mixed population or on a network. Many epidemics, however, are hybrid, employing more than one spreading mechanism. For example, the Internet worm Conficker spreads locally targeting neighbouring computers in local networks as well as globally by randomly probing any computer on the Inter...

The Zika epidemic and abortion in Latin America: a scoping review.

Science.gov (United States)

Carabali, Mabel; Austin, Nichole; King, Nicholas B; Kaufman, Jay S

2018-01-01

Latin America presently has the world's highest burden of Zika virus, but there are unexplained differences in national rates of congenital malformations collectively referred to as Congenital Zika Syndrome (CZS) in the region. While Zika virulence and case detection likely contribute to these differences, policy-related factors, including access to abortion, may play important roles. Our goal was to assess perspectives on, and access to, abortion in Latin America in the context of the Zika epidemic. We conducted a scoping review of peer-reviewed and gray literature published between January 2015 and December 2016, written in English, Spanish, Portuguese, or French. We searched PubMed, Scielo, and Google Scholar for literature on Zika and/or CZS and abortion, and used automated and manual review methods to synthesize the existing information. 36 publications met our inclusion criteria, the majority of which were qualitative. Publications were generally in favor of increased access to safe abortion as a policy-level response for mitigating the impact of CZS, but issues with implementation were cited as the main challenge. Aside from the reform of abortion regulation in Colombia, we did not find evidence that the Zika epidemic had triggered shifts in abortion policy in other countries. Abortion policy in the region remained largely unchanged following the Zika epidemic. Further empirical research on abortion access and differential rates of CZS across Latin American countries is required.

A geographic information system for the study of past epidemics: The 1705 epidemic in Martigues (Bouches-du-Rhône, France

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Stéfan Tzortzis

2012-01-01

Full Text Available At the beginning of the 18th century, the Provence region was hit by several severe epidemics whose causes are still not clearly understood.To draw up epidemic profiles and to identify the pathogenic agents concerned, we constituted a large onomastic database and built ageographic information system for Martigues, a medium-sized community in the south of France. The cross-linking of epidemiological,spatial and demographical data allows us to propose a new diagnosis for the epidemic which reached Martigues in the autumn of 1705.

The levelling off of the obesity epidemic since the year 1999--a review of evidence and perspectives

DEFF Research Database (Denmark)

Rokholm, B; Baker, J L; Sørensen, T I A

2010-01-01

The purpose was to investigate a possible levelling off in the obesity epidemic, by systematically reviewing literature and web-based sources. Eligible studies and data sources were required to have at least two measures of obesity prevalence since 1999. A literature and Internet search resulted...... obesity trends to identify the driving forces behind the epidemic. It is important to emphasize that the levelling off is not tantamount to calling off the epidemic. Additionally, it is worthwhile to keep in mind that previous stable phases have been followed by further increases in the prevalence...

Stochastic population and epidemic models persistence and extinction

CERN Document Server

Allen, Linda J S

2015-01-01

This monograph provides a summary of the basic theory of branching processes for single-type and multi-type processes. Classic examples of population and epidemic models illustrate the probability of population or epidemic extinction obtained from the theory of branching processes. The first chapter develops the branching process theory, while in the second chapter two applications to population and epidemic processes of single-type branching process theory are explored. The last two chapters present multi-type branching process applications to epidemic models, and then continuous-time and continuous-state branching processes with applications. In addition, several MATLAB programs for simulating stochastic sample paths  are provided in an Appendix. These notes originated as part of a lecture series on Stochastics in Biological Systems at the Mathematical Biosciences Institute in Ohio, USA. Professor Linda Allen is a Paul Whitfield Horn Professor of Mathematics in the Department of Mathematics and Statistics ...

Theoretical basis to measure the impact of short-lasting control of an infectious disease on the epidemic peak

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Omori Ryosuke

2011-01-01

Full Text Available Abstract Background While many pandemic preparedness plans have promoted disease control effort to lower and delay an epidemic peak, analytical methods for determining the required control effort and making statistical inferences have yet to be sought. As a first step to address this issue, we present a theoretical basis on which to assess the impact of an early intervention on the epidemic peak, employing a simple epidemic model. Methods We focus on estimating the impact of an early control effort (e.g. unsuccessful containment, assuming that the transmission rate abruptly increases when control is discontinued. We provide analytical expressions for magnitude and time of the epidemic peak, employing approximate logistic and logarithmic-form solutions for the latter. Empirical influenza data (H1N1-2009 in Japan are analyzed to estimate the effect of the summer holiday period in lowering and delaying the peak in 2009. Results Our model estimates that the epidemic peak of the 2009 pandemic was delayed for 21 days due to summer holiday. Decline in peak appears to be a nonlinear function of control-associated reduction in the reproduction number. Peak delay is shown to critically depend on the fraction of initially immune individuals. Conclusions The proposed modeling approaches offer methodological avenues to assess empirical data and to objectively estimate required control effort to lower and delay an epidemic peak. Analytical findings support a critical need to conduct population-wide serological survey as a prior requirement for estimating the time of peak.

Climate drives the meningitis epidemics onset in west Africa.

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Benjamin Sultan

2005-01-01

Full Text Available BACKGROUND: Every year West African countries within the Sahelo-Sudanian band are afflicted with major meningococcal meningitis (MCM disease outbreaks, which affect up to 200,000 people, mainly young children, in one of the world's poorest regions. The timing of the epidemic year, which starts in February and ends in late May, and the spatial distribution of disease cases throughout the "Meningitis Belt" strongly indicate a close linkage between the life cycle of the causative agent of MCM and climate variability. However, mechanisms responsible for the observed patterns are still not clearly identified. METHODS AND FINDINGS: By comparing the information on cases and deaths of MCM from World Health Organization weekly reports with atmospheric datasets, we quantified the relationship between the seasonal occurrence of MCM in Mali, a West African country, and large-scale atmospheric circulation. Regional atmospheric indexes based on surface wind speed show a clear link between population dynamics of the disease and climate: the onset of epidemics and the winter maximum defined by the atmospheric index share the same mean week (sixth week of the year; standard deviation, 2 wk and are highly correlated. CONCLUSIONS: This study is the first that provides a clear, quantitative demonstration of the connections that exist between MCM epidemics and regional climate variability in Africa. Moreover, this statistically robust explanation of the MCM dynamics enables the development of an Early Warning Index for meningitis epidemic onset in West Africa. The development of such an index will undoubtedly help nationwide and international public health institutions and policy makers to better control MCM disease within the so-called westward-eastward pan-African Meningitis Belt.

The impact of generalized and institutional trust on donating to activist, leisure, and interest organizations: individual and contextual effects

NARCIS (Netherlands)

Evers, A.B.; Gesthuizen, M.J.W.

2011-01-01

In this paper, we answer the question as to what extent donating to activist, interest, and leisure organizations is affected by both individual and national levels of generalized and institutional trust. We use the European Social Survey 2002 to estimate multilevel random intercept models, based on

[The concept of health in the General Health Law (1986)].

Science.gov (United States)

Peral, D

1993-01-01

The 1986 "Le General de Sanidad" (Sanitary General Regulations) has been studied using the method of the "Topología del Discurso" in order to elucidate what are the thoughts of the lawmakers. The law protects not only the population of catastrophes as it happened with the choleric epidemic of the XIX century, but considers a new concept a sanitary wealth should be provided to the individuals. Together with this new concept there are new ones such as equality and universalization of the sanitary assistence that would be keys of the aim of the lawmakers: to coordinate all the State resources in the reform of the spanish sanity. This includes the integration of the Universities. This can help in the understanding of the dificulties in the development and aplication of the Law present reality.

Is the New Heroin Epidemic Really New? Racializing Heroin.

Science.gov (United States)

Bowser, Benjamin; Fullilove, Robert; Word, Carl

2017-01-01

Heroin abuse as an outcome of the prior use of painkillers increased rapidly over the past decade. This "new epidemic" is unique because the new heroin users are primarily young White Americans in rural areas of virtually every state. This commentary argues that the painkiller-to-heroin transition could not be the only cause of heroin use on such a scale and that the new and old heroin epidemics are linked. The social marketing that so successfully drove the old heroin epidemic has innovated and expanded due to the use of cell-phones, text messaging and the "dark web" which requires a Tor browser, and software that allows one to communicate with encrypted sites without detection. Central city gentrification has forced traffickers to take advantage of larger and more lucrative markets. A second outcome is that urban black and Latino communities are no longer needed as heroin stages areas for suburban and exurban illicit drug distribution. Drug dealing can be done directly in predominantly white suburbs and rural areas without the accompanying violence associated with the old epidemic. Denial of the link between the new and old heroin epidemics racially segregates heroin users and more proactive prevention and treatment in the new epidemic than in the old. It also cuts off a half-century of knowledge about the supply-side of heroin drug dealing and the inevitable public policy measures that will have to be implemented to effectively slow and stop both the old and new epidemic. Copyright © 2016 National Medical Association. Published by Elsevier Inc. All rights reserved.

Functional form comparison between the population and the individual Poisson based TCP models

International Nuclear Information System (INIS)

Schinkel, C.; Stavreva, N.; Stavrev, P.; Carlone, M.; Fallone, B.G.

2007-01-01

In this work, the functional form similarity between the individual and fundamental population TCP models is investigated. Using the fact that both models can be expressed in terms of the geometric parameters γ 50 and D 50 , we show that they have almost identical functional form for values of γ 50 ≥1. The conceptual inadequacy of applying an individual model to clinical data is also discussed. A general individual response TCP expression is given, parameterized by D f and γ f - the dose corresponding to a control level of f, and the normalized slope at that point. It is shown that the dose-response may be interpreted as an individual response only if γ 50 is sufficiently high. Based on the functional form equivalency between the individual and the population TCP models, we discuss the possibility of applying the individual TCP model for the case of heterogeneous irradiations. Due to the fact that the fundamental population TCP model is derived for homogeneous irradiations only, we propose the use of the EUD, given by the generalized mean dose, when the fundamental population TCP model is used to fit clinical data. (author)

Spatial spread of an epidemic through public transportation systems with a hub.

Science.gov (United States)

Xu, Fei; Connell McCluskey, C; Cressman, Ross

2013-11-01

This article investigates an epidemic spreading among several locations through a transportation system, with a hub connecting these locations. Public transportation is not only a bridge through which infections travel from one location to another but also a place where infections occur since individuals are typically in close proximity to each other due to the limited space in these systems. A mathematical model is constructed to study the spread of an infectious disease through such systems. A variant of the next generation method is proposed and used to provide upper and lower bounds of the basic reproduction number for the model. Our investigation indicates that increasing transportation efficiency, and improving sanitation and ventilation of the public transportation system decrease the chance of an outbreak occurring. Moreover, discouraging unnecessary travel during an epidemic also decreases the chance of an outbreak. However, reducing travel by infectives while allowing susceptibles to travel may not be enough to avoid an outbreak. Copyright © 2013 Elsevier Inc. All rights reserved.

Critical behavior in a stochastic model of vector mediated epidemics

Science.gov (United States)

Alfinito, E.; Beccaria, M.; Macorini, G.

2016-06-01

The extreme vulnerability of humans to new and old pathogens is constantly highlighted by unbound outbreaks of epidemics. This vulnerability is both direct, producing illness in humans (dengue, malaria), and also indirect, affecting its supplies (bird and swine flu, Pierce disease, and olive quick decline syndrome). In most cases, the pathogens responsible for an illness spread through vectors. In general, disease evolution may be an uncontrollable propagation or a transient outbreak with limited diffusion. This depends on the physiological parameters of hosts and vectors (susceptibility to the illness, virulence, chronicity of the disease, lifetime of the vectors, etc.). In this perspective and with these motivations, we analyzed a stochastic lattice model able to capture the critical behavior of such epidemics over a limited time horizon and with a finite amount of resources. The model exhibits a critical line of transition that separates spreading and non-spreading phases. The critical line is studied with new analytical methods and direct simulations. Critical exponents are found to be the same as those of dynamical percolation.

Epidemics and rumours in complex networks

CERN Document Server

Draief, Moez

2009-01-01

Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling

A Method to Estimate the Size and Characteristics of HIV-positive Populations Using an Individual-based Stochastic Simulation Model

DEFF Research Database (Denmark)

Nakagawa, Fumiyo; van Sighem, Ard; Thiebaut, Rodolphe

2016-01-01

% plausibility range: 39,900-45,560) men who have sex with men were estimated to be living with HIV in the UK, of whom 10,400 (6,160-17,350) were undiagnosed. There were an estimated 3,210 (1,730-5,350) infections per year on average between 2010 and 2013. Sixty-two percent of the total HIV-positive population......It is important not only to collect epidemiologic data on HIV but to also fully utilize such information to understand the epidemic over time and to help inform and monitor the impact of policies and interventions. We describe and apply a novel method to estimate the size and characteristics of HIV-positive...... populations. The method was applied to data on men who have sex with men living in the UK and to a pseudo dataset to assess performance for different data availability. The individual-based simulation model was calibrated using an approximate Bayesian computation-based approach. In 2013, 48,310 (90...

Suppressing traffic-driven epidemic spreading by use of the efficient routing protocol

International Nuclear Information System (INIS)

Yang, Han-Xin; Wu, Zhi-Xi

2014-01-01

Despite extensive work on the interplay between traffic dynamics and epidemic spreading, the control of epidemic spreading by routing strategies has not received adequate attention. In this paper, we study the impact of an efficient routing protocol on epidemic spreading. In the case of infinite node-delivery capacity, where the traffic is free of congestion, we find that that there exist optimal values of routing parameter, leading to the maximal epidemic threshold. This means that epidemic spreading can be effectively controlled by fine tuning the routing scheme. Moreover, we find that an increase in the average network connectivity and the emergence of traffic congestion can suppress the epidemic outbreak. (paper)

Canine distemper virus infection among wildlife before and after the epidemic.

Science.gov (United States)

Suzuki, Junko; Nishio, Yohei; Kameo, Yuki; Terada, Yutaka; Kuwata, Ryusei; Shimoda, Hiroshi; Suzuki, Kazuo; Maeda, Ken

2015-11-01

In 2007-2008, a canine distemper virus (CDV) epidemic occurred among wild animals in Wakayama Prefecture, Japan, and many mammals, including the wild boar and deer, were infected. In this study, CDV prevalence among wild animals was surveyed before and after the epidemic. At first, an enzyme-linked immunosorbent assay (ELISA) with horseradish peroxidase-conjugated protein A/G was established to detect CDV antibodies in many mammalian species. This established ELISA was available for testing dogs, raccoons and raccoon dogs as well as virus-neutralization test. Next, a serological survey of wild mammalians was conducted, and it was indicated that many wild mammalians, particularly raccoons, were infected with CDV during the epidemic, but few were infected before and after the epidemic. On the other hand, many raccoon dogs died during the epidemic, but CDV remained prevalent in the remaining population, and a small epidemic occurred in raccoon dogs in 2012-2013. These results indicated that the epidemic of 2007-2008 may have been intensified by transmission to raccoons.

Effects of contact network structure on epidemic transmission trees: implications for data required to estimate network structure.

Science.gov (United States)

Carnegie, Nicole Bohme

2018-01-30

Understanding the dynamics of disease spread is key to developing effective interventions to control or prevent an epidemic. The structure of the network of contacts over which the disease spreads has been shown to have a strong influence on the outcome of the epidemic, but an open question remains as to whether it is possible to estimate contact network features from data collected in an epidemic. The approach taken in this paper is to examine the distributions of epidemic outcomes arising from epidemics on networks with particular structural features to assess whether that structure could be measured from epidemic data and what other constraints might be needed to make the problem identifiable. To this end, we vary the network size, mean degree, and transmissibility of the pathogen, as well as the network feature of interest: clustering, degree assortativity, or attribute-based preferential mixing. We record several standard measures of the size and spread of the epidemic, as well as measures that describe the shape of the transmission tree in order to ascertain whether there are detectable signals in the final data from the outbreak. The results suggest that there is potential to estimate contact network features from transmission trees or pure epidemic data, particularly for diseases with high transmissibility or for which the relevant contact network is of low mean degree. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Spreading dynamics on complex networks: a general stochastic approach.

Science.gov (United States)

Noël, Pierre-André; Allard, Antoine; Hébert-Dufresne, Laurent; Marceau, Vincent; Dubé, Louis J

2014-12-01

Dynamics on networks is considered from the perspective of Markov stochastic processes. We partially describe the state of the system through network motifs and infer any missing data using the available information. This versatile approach is especially well adapted for modelling spreading processes and/or population dynamics. In particular, the generality of our framework and the fact that its assumptions are explicitly stated suggests that it could be used as a common ground for comparing existing epidemics models too complex for direct comparison, such as agent-based computer simulations. We provide many examples for the special cases of susceptible-infectious-susceptible and susceptible-infectious-removed dynamics (e.g., epidemics propagation) and we observe multiple situations where accurate results may be obtained at low computational cost. Our perspective reveals a subtle balance between the complex requirements of a realistic model and its basic assumptions.

Invited review: Epidemics on social networks

Directory of Open Access Journals (Sweden)

M. N. Kuperman

2013-01-01

Full Text Available Since its first formulations almost a century ago, mathematical models fordisease spreading contributed to understand, evaluate and control the epidemic processes.They promoted a dramatic change in how epidemiologists thought of the propagation of infectious diseases.In the last decade, when the traditional epidemiological models seemed to be exhausted, new types of models were developed.These new models incorporated concepts from graph theory to describe and model the underlying social structure.Many of these works merely produced a more detailed extension of the previous results, but some otherstriggered a completely new paradigm in the mathematical study of epidemic processes. In this review, we will introduce the basicconcepts of epidemiology, epidemic modeling and networks, to finally provide a brief description of the mostrelevant results in the field.Received: 6 April 2013, Accepted: 3 June 2013; Edited by: G. Mindlin; DOI: http://dx.doi.org/10.4279/PIP.050003Cite as: M N Kuperman, Papers in Physics 5, 050003 (2013

A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy.

Science.gov (United States)

Zakary, Omar; Rachik, Mostafa; Elmouki, Ilias

2017-08-01

First, we devise in this paper, a multi-regions discrete-time model which describes the spatial-temporal spread of an epidemic which starts from one region and enters to regions which are connected with their neighbors by any kind of anthropological movement. We suppose homogeneous Susceptible-Infected-Removed (SIR) populations, and we consider in our simulations, a grid of colored cells, which represents the whole domain affected by the epidemic while each cell can represent a sub-domain or region. Second, in order to minimize the number of infected individuals in one region, we propose an optimal control approach based on a travel-blocking vicinity strategy which aims to control only one cell by restricting movements of infected people coming from all neighboring cells. Thus, we show the influence of the optimal control approach on the controlled cell. We should also note that the cellular modeling approach we propose here, can also describes infection dynamics of regions which are not necessarily attached one to an other, even if no empty space can be viewed between cells. The theoretical method we follow for the characterization of the travel-locking optimal controls, is based on a discrete version of Pontryagin's maximum principle while the numerical approach applied to the multi-points boundary value problems we obtain here, is based on discrete progressive-regressive iterative schemes. We illustrate our modeling and control approaches by giving an example of 100 regions.

Epidemic spreading through direct and indirect interactions.

Science.gov (United States)

Ganguly, Niloy; Krueger, Tyll; Mukherjee, Animesh; Saha, Sudipta

2014-09-01

In this paper we study the susceptible-infected-susceptible epidemic dynamics, considering a specialized setting where popular places (termed passive entities) are visited by agents (termed active entities). We consider two types of spreading dynamics: direct spreading, where the active entities infect each other while visiting the passive entities, and indirect spreading, where the passive entities act as carriers and the infection is spread via them. We investigate in particular the effect of selection strategy, i.e., the way passive entities are chosen, in the spread of epidemics. We introduce a mathematical framework to study the effect of an arbitrary selection strategy and derive formulas for prevalence, extinction probabilities, and epidemic thresholds for both indirect and direct spreading. We also obtain a very simple relationship between the extinction probability and the prevalence. We pay special attention to preferential selection and derive exact formulas. The analysis reveals that an increase in the diversity in the selection process lowers the epidemic thresholds. Comparing the direct and indirect spreading, we identify regions in the parameter space where the prevalence of the indirect spreading is higher than the direct one.

The fastest spreader in SIS epidemics on networks

NARCIS (Netherlands)

He, Z.; Van Mieghem, P.F.A.

2018-01-01